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  • 1.
    Athanassiadis, Dimitris
    et al.
    Dept. of Forest Resource Management, Swedish University of Agricultural Sciences.
    Bergström, Dan
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Lindroos, Ola
    Dept. of Forest Resource Management, Swedish University of Agricultural Sciences.
    Nordfjell, Tomas
    Dept. of Forest Resource Management, Swedish University of Agricultural Sciences.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Path tracking for autonomous forwarders in forest terrain2010Ingår i: Precision Forestry Symposium: developments in Precision Forestry since 2006 / [ed] Ackerman P A, Ham H, & Lu C, 2010, s. 42-43Konferensbidrag (Refereegranskat)
  • 2.
    Barth, Ruud
    et al.
    Greenhouse Horticulture, Wageningen University & Research Center.
    Baur, Jörg
    Institute of Applied Mechanics, Technische Universität München.
    Buschmann, Thomas
    Institute of Applied Mechanics, Technische Universität München.
    Edan, Yael
    Department of Industrial Engineering and Management, Ben-Gurion University of the Negev.
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Nguyen, Thanh
    KU Leuven, Department of Biosystems.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Saeys, Wouter
    KU Leuven, Department of Biosystems.
    Salinas, Carlota
    Centre for Automation and Robotics UPM-CSIC.
    Vitzrabin, Efi
    Department of Industrial Engineering and Management, Ben-Gurion University of the Negev.
    Using ROS for agricultural robotics: design considerations and experiences2014Ingår i: RHEA-2014 / [ed] Pablo Gonzalez-de-Santos and Angela Ribeiro, 2014, s. 509-518Konferensbidrag (Refereegranskat)
    Abstract [en]

    We report on experiences of using the ROS middleware for developmentof agricultural robots. We describe software related design considerations for all maincomponents in developed subsystems as well as drawbacks and advantages with thechosen approaches. This work was partly funded by the European Commission(CROPS GA no 246252).

  • 3. Bontsema, J.
    et al.
    Hemming, J.
    Pekkeriet, E.
    Saeys, W.
    Edan, Y.
    Shapiro, A.
    Hočevar, M.
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Oberti, R.
    Armada, M.
    Ulbrich, H.
    Baur, J.
    Debilde, B.
    Best, S.
    Evain, S.
    Gauchel, W.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    CROPS: high tech agricultural robots2014Konferensbidrag (Övrigt vetenskapligt)
  • 4. Bontsema, Jan
    et al.
    Hemming, Jochen
    Pekkeriet, Erik
    Saeys, Wouter
    Edan, Yael
    Shapiro, Amir
    Hočevar, Marko
    Oberti, Roberto
    Armada, Manuel
    Ulbrich, Heinz
    Baur, Jörg
    Debilde, Benoit
    Best, Stanley
    Evain, Sébastien
    Gauchel, Wolfgang
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    CROPS: Clever Robots for Crops2015Ingår i: Engineering & Technology Reference, ISSN 2056-4007, Vol. 1, nr 1Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In the EU-funded CROPS project robots are developed for site-specific spraying and selective harvesting of fruit and fruit vegetables. The robots are being designed to harvest crops, such as greenhouse vegetables, apples, grapes and for canopy spraying in orchards and for precision target spraying in grape vines. Attention is paid to the detection of obstacles for autonomous navigation in a safe way in plantations and forests. For the different applications, platforms were built. Sensing systems and vision algorithms have been developed. For software the Robot Operating System is used. A 9 degrees of freedom manipulator was designed and tested for sweet-pepper harvesting, apple harvesting and in close range spraying. For the applications different end-effectors were designed and tested. For sweet pepper a platform that can move in between the crop rows on the common greenhouse rail system which also serves as heating pipes was built. The apple harvesting platform is based on a current mechanical grape harvester. In discussion with growers so-called ‘walls of fruit trees’ have been designed which bring robots closer to the practice. A canopy-optimised sprayer has been designed as a trailed sprayer with a centrifugal blower. All the applications have been tested under practical conditions.

  • 5.
    Georgsson, Fredrik
    et al.
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Johansson, Thomas
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Prorok, Kalle
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Tillämpad fysik och elektronik.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Sandström, Urban
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Development of an Autonomous Path Tracking Forest Machine: a status report2005Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In many respects traditional automation in the forest-machine industry has reached an up- per limit, since the driver already has to deal with an excess of information and take too many decisions at a very high pace. To further automation still, introduction of semi-autonomous and autonomous functions are expected and considered necessary. This paper describes an ongoing project along these ideas. We describe the development of the hardware and software of an unmanned shuttle that shifts timber from the area of felling to the main roads for fur- ther transportation. A new path-tracking algorithm is introduced, and demonstrated as being superior to standard techniques, such as Follow-the-Carrot and Pure-Pursuit. To facilitate the research and development, a comprehensive software architecture for sensor and actuator interfacing is developed. Obstacle avoidance is accomplished by a new kind of radar, developed for and by the automotive industry. Localization is accomplished by a Kalman filter combining data from a Real-Time Kinematic Differential GPS/GLONASS and a gyro/compass. Tests conducted on a simulator and a small-scale robot show promising results. Tests on the real forest machine are ongoing, and will be completed before the end of 2005.

  • 6.
    Hellström, Thomas
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hohnloser, Peter
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Tree diameter estimation using laser scanner2012Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Accurate vehicle localization in forest environments is still an unresolved problem. GPS has obvious limitations in dense forest, and has to be mixed with other techniques to provide satisfying solutions. One possible way is to localize the vehicle relative to trees detected around the vehicle. The first step to implement this method is is to find reliable methods to detect trees, and also to match them to maps. The reliability of this matching operation is improved by accurate estimations of tree diameter. In this paper we evaluate a number of existing algorithms for detection of trees and estimation of tree diameter. Three new algorithms are also suggested. All algorithms were evaluated in field experiments at three different locations with varying tree trunk visibility. The results show that one of the existing algorithms is clearly less reliable than the other two. Noticeable is that the existing algorithms often overestimate tree trunk diameter. The new algorithms mostly underestimate, but are most accurate in some situations. 

  • 7.
    Hellström, Thomas
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Johansson, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    A Java-based middleware for control and sensing in mobile robotics2008Ingår i: International Conference on Intelligent Automation and Robotics 2008, 2008, s. 649-654Konferensbidrag (Refereegranskat)
    Abstract [en]

    Many of the existing mobile-robot software packages do not include handling of sensors and actuators in a sufficiently systematic and uniform way, as described later in this section. The software framework proposed in this paper, denoted NAV2000, addresses the specific need for interchangeability of components in robotics. At the lowest level, sensors, and sometimes also actuators, often have to be replaced by similar, yet not identical, components. At a higher level, the target vehicle often changes during the work process. The presented software provides a framework that supports these replacements and allows configurations of sensors, actuators, and target machines to be specified and manipulated in an efficient manner. The system can be distributed over a network of computers if some software modules require more computing power, i.e. more hardware can be added to the system without any software changes. To accomplish sufficient monitoring of the system's health, a dedicated system keeps track of all software modules. The system uses logfiles to enable convenient debugging and performance analysis of hardware and software modules. The software has been developed as part of, and is currently in use in, a R&D-project for an autonomous path-tracking forest machine.

  • 8.
    Hellström, Thomas
    et al.
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Johansson, Thomas
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    A Software Framework for Control and Sensing in Mobile Robotics2007Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Many of the existing mobile-robot softwares do not include handling of sensors and actuators in a sufficiently systematic and uniform way. The software framework proposed in this paper addresses the specific need for interchangeability of components in robotics. At the lowest level, sensors, and sometimes also actuators, often have to be replaced by similar, yet not identical, components. At a higher level, the target vehicle for the developed system often changes during the work process. The presented software provides a framework that supports these replacements and allows configurations of sensors, actuators, and target machines to be specified and manipulated in an efficient manner. The system can be run on several different computers if some software modules require more computing power. To accomplish sufficient monitoring of the system's health, a dedicated system keeps track of all software modules loaded onto the local computer, and also communicates with health monitors in all other computers running the system. The overall health of every module as well as a more detailed description of possible problems is presented graphically. In addition to this, the system uses logfiles to enable convenient debugging and performance analysis of hardware and software modules. The software has been developed as part of, and is currently in use in, a R&D-project for an autonomous path-tracking forest machine.

  • 9.
    Hellström, Thomas
    et al.
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Johansson, Thomas
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Development of an Autonomous Forest Machine for Path Tracking2006Ingår i: Field and Service Robotics: Results of the 5th International Conference, New York: Springer , 2006, s. 603-614Konferensbidrag (Refereegranskat)
    Abstract [en]

    In many respects traditional automation in the forest-machine industry hasreached an upper limit, since the driver already has to deal with an excess ofinformation and take too many decisions at a very high pace. To furtherautomation still, introduction of semi-autonomous and autonomous functions areexpected and considered necessary. This paper describes an ongoing projectalong these ideas. We describe the development of the hardware and software ofan unmanned shuttle that shifts timber from the area of felling to the mainroads for further transportation. A new path-tracking algorithm is introduced,and demonstrated as being superior to standard techniques, such as Follow theCarrot and Pure Pursuit. To facilitate the research and development, acomprehensive software architecture for sensor and actuator interfacing isdeveloped. Obstacle avoidance is accomplished by a new kind of radar,developed for and by the automotive industry. Localization is accomplished by combining data from a Real-Time Kinematic DifferentialGPS/GLONASS and odometry. Tests conducted on a simulator and asmall-scale robot show promising results. Tests on the real forest machine areongoing.

  • 10.
    Hellström, Thomas
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Lärkeryd, Per
    Indexator .
    Nordfjell, Tomas
    Department of Forest Resource Management, Swedish University of Agricultural Sciences.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Autonomous forest vehicles: historic, envisioned, and state-of-the-art2009Ingår i: International Journal of Forest Engineering, ISSN 1494-2119, E-ISSN 1913-2220, Vol. 20, nr 1, s. 33-38Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The feasibility of using autonomous forest vehicles (which can be regarded as logical developments in the ongoing automation of forest machines), the systems that could be applied in them, their potential advantages and their limitations (in the foreseeable future) are considered here. The aims were to analyse: (1) the factors influencing the degree of automation in logging; (2) the technical principles that can be applied to autonomous forest machines, and (3) the feasibility of developing an autonomous path-tracking forest vehicle. A type of vehicle that is believed to have considerable commercial potential is an autonomous forwarder. The degree of automation is influenced by increased productivity, the machine operator as a bottle-neck, cost reduction, and environmental aspects. Technical principles that can be applied to autonomous forest vehicles are satellite navigation, wheel odometry, laser scanner and radar. A new path-tracking algorithm has been developed to reduce deviations from the desired path by utilizing the driver’s steering commands. The presented system has demonstrated both possibilities and difficulties associated with autonomous forest machines. It is in a field study shown that it is quite possible for them to learn and track a path previously demonstrated by an operator with an accuracy of 0.1m on flat ground and also to detect and avoid unexpected obstacles. Although the forest machine safely avoids obstacles, the study shows that further research in the field of obstacle avoidance is needed to optimize performance and ensure safe operation in a real forest environment.

  • 11.
    Hellström, Thomas
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Lärkeryd, Pär
    Nordfjell, Thomas
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Autonomous forest machines: Past present and future2008Rapport (Övrigt vetenskapligt)
    Abstract [en]

    The feasibility of using autonomous forest vehicles (which can be regarded as logical developments in the ongoing automation of forest machines), the systems that could be applied in them, their potential advantages and their limitations (in the foreseeable future) are considered here. The aims were to analyse: (1) the factors influencing the degree of automation in logging; (2) the technical principles that can be applied to autonomous forest machines, and (3) the feasibility of developing an autonomous path-tracking forest vehicle. A class of such vehicles that are believed to have considerable commercial potential is autonomous wood shuttles (forwarders). The degree of automation is influenced by increased productivity, the machine operator as a bottle-neck, cost reduction, and environmental aspects. Technical principles that can be applied to autonomous forest vehicles are satellite navigation, laser odometry, wheel odometry, laser scanner and radar. The presented system has demonstrated both possibilities and difficulties associated with autonomous forest machines. It is in a field study shown that it is quite possible for them to learn and track a path previously demonstrated by an operator with an accuracy of 0.1m on flat ground. A new pathtracking algorithm has been developed to reduce deviations by utilizing the driver’s steering commands.

  • 12.
    Hellström, Thomas
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    A software framework for agricultural and forestry robotics2012Ingår i: Proceedings of the first International Conference on Robotics and associated High-technologies and Equipment for agriculture: Applications of automated systems and robotics for crop protection in sustainable precision agriculture / [ed] Andrea Peruzzi, Pisa: Pisa University Press , 2012, s. 171-176Konferensbidrag (Refereegranskat)
    Abstract [en]

    In  this  paper  we  describe  on-going  development  of  a  generic software framework for development of agricultural and forestry robots.  The  goal  is  to  provide  generic  high-level  functionality and to encourage distributed and structured programming, thus leading to faster and simplified development of robots. Different aspects  of  the  framework  are  described  using  different architecture views.  We show how these views complement each other  in  a  way  that  supports  development  and  description  of robot software. 

  • 13.
    Hellström, Thomas
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    A software framework for agricultural and forestry robots2013Ingår i: Industrial robot, ISSN 0143-991X, E-ISSN 1758-5791, Vol. 40, nr 1, s. 20-26Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Purpose: The purpose of this paper is to describe a generic software framework for development of agricultural and forestry robots. The primary goal is to provide generic high-level functionality and to encourage distributed and structured programming, thus leading to faster and simplified development of robots. A secondary goal is to investigate the value of several architecture views when describing different software aspects of a robotics system.

    Design/methodology/approach: The framework is constructed with a hybrid robot architecture, with a static state machine that implements a flow diagram describing each specific robot. Furthermore, generic modules for GUI, resource management, performance monitoring, and error handling are included. The framework is described with logical, development, process, and physical architecture views.

    Findings: The multiple architecture views provide complementary information that is valuable both during and after the design phase. The framework has been shown to be efficient and time saving when integrating work by several partners in several robotics projects. Although the framework is guided by the specific needs of harvesting agricultural robots, the result is believed to be of general value for development also of other types of robots.

    Originality/value: In this paper, the authors present a novel generic framework for development of agricultural and forestry robots. The robot architecture uses a state machine as replacement for the planner commonly found in other hybrid architectures. The framework is described with multiple architecture views.

  • 14.
    Hellström, Thomas
    et al.
    Umeå universitet.
    Ringdahl, Ola
    Umeå universitet.
    Autonomous Path Tracking Using Recorded Orientation and Steering Commands2005Ingår i: Proceedings of Towards Autonomous Robotic Systems 2005 (TAROS05), 2005Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper describes a novel algorithm, Follow-the-Past, for autonomous path-tracking vehicles. Common algorithms, like Pure Pursuit and Follow the Carrot, compute steering commands that make a vehicle follow approximately a predefined path. One problem with these algorithms is that they tend to cut corners, since they do not explicitly take into account the actual curvature of the path. The method presented in this paper uses recorded orientation and steering commands to overcome this problem. The algorithm is constructed within the reactive paradigm, common in modern robotics, and is divided into three separate behaviors, each responsible for one aspect of the path-tracking task. We present results from both a simulator for autonomous forest machines and experiments with a physical robot. The results are compared with the Pure-Pursuit and the Follow-the-Carrot algorithms, and show a significant improvement in performance.

  • 15.
    Hellström, Thomas
    et al.
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Follow The Past: a Path Tracking Algorithm for Autonomous Forest Vehicles2004Rapport (Övrigt vetenskapligt)
    Abstract [en]

    A number of algorithms for path tracking are described in the robotics literature. Traditional algorithms like Pure Pursuit and Follow the Carrot use position information to compute steering commands that make a vehicle approximately follow a predefined path. These algorithms are well known to cut corners since they do not explicitly take into account the actual curvature of the path. In this paper we present a novel algorithm that uses recorded steering commands to overcome this problem. The algorithm is constructed within the behavioural paradigm, and is divided into three separate behaviours, each one responsible for one aspect of the path tracking task. The algorithm is implemented in a simulator for forest machines and the results are compared with the Pure Pursuit and the Follow the Carrot algorithms. The results show a significant improvement in performance, both for ideal noise free position data, and also for position data with added simulated noise.

  • 16.
    Hellström, Thomas
    et al.
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Follow the Past: a Path Tracking Algorithm for Autonomous Vehicles2006Ingår i: International Journal of Vehicle Autonomous Systems, ISSN 1741-5306, Vol. 4, nr 2/3/4, s. 216-224Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A number of algorithms for path tracking are described in the robotics literature. Traditional algorithms, like Pure Pursuit and Follow the Carrot, use position information to compute steering commands that make a vehicle follow a pre-defined path approximately. These algorithms are well known to cut corners, since they do not explicitly take into account the actual curvature of the path. In this paper we present a novel algorithm that uses recorded steering commands to overcome this problem. The algorithm is constructed within the behavioural paradigm common in intelligent robotics and is divided into three separate behaviours, each responsible for one aspect of the path-tracking task. The algorithm is implemented both on a simulator for autonomous forest machines and a physical small-scale robot. The results are compared with the Pure Pursuit and the Follow the Carrot algorithms and show a significant improvement in performance.

  • 17.
    Hellström, Thomas
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Path planning for off-road vehicles with a simulator-in-the-loop2008Rapport (Övrigt vetenskapligt)
    Abstract [en]

    This paper describes the development of a real-time path planner for off-road vehicles using a simulator. The work was triggered by a need for an obstacle-avoidance and path-planning system in our work with autonomous forest machines. The general idea with the presented system is to extend a standard path-tracking algorithm with a simulator that, in real-time, tries to predict collisions in a window forward in time. This simulation is based on current sensor data giving information about the environment around the vehicle. If a collision is predicted, the vehicle is stopped and a path-search phase is initiated. Variants of the original path are generated and simulated until a feasible path is found. The real vehicle then continues, now tracking the replanned path. In simulated tests, this way of using a simulator to predict and avoid collisions works well. The system is able to safely navigate around obstacles on and close to the path in a way that is hard or impossible to achieve with standard obstacle-avoidance algorithms that do not take the shape of the vehicle into account. Another scenario, also envisioned in forest environment, is off-line path planning of a longer route, based on map information. An approximate path given by a straight line from start to goal is then modified in the same way as described above.

  • 18.
    Hellström, Thomas
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Real-time path planning using a simulator-in-the-loop2009Ingår i: International Journal Vehicle Autonomous Systems, ISSN 1471-0226, Vol. 7, nr 1/2, s. 56-72Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper describes the development of a real-time path planner for off-road vehicles using a simulator. The general idea with the presented system is to extend a standard path-tracking algorithm with a simulator that, in real-time, tries to predict collisions in a window forward in time. If a collision is predicted, the vehicle is stopped and a path-search phase is initiated. Variants of the original path are generated and simulated until a feasible path is found. The real vehicle then continues, now tracking the replanned path.

  • 19.
    Hellström, Thomas
    et al.
    Umeå universitet.
    Ringdahl, Ola
    Umeå universitet.
    Siddiqui, Arsalan
    Path tracking and localization techniques for forest environment.2006Ingår i: Proceedings of the Israel Conference on Robotics (ICR06), 2006Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    This paper describes an ongoing design and development project of an autonomous patht-racking forest machine. The work is part of a long-term vision in the forest industry of developing an unmanned shuttle that transports timber from the felling area to the main roads for further transportation. The developed prototype system has two modes of operation: Path Learning, in which the human operator drives or remote controls the vehicle along a selected path back and forth from the area of felling to the transportation road. In this phase, position, speed, heading, and the operator’s commands are recorded in the vehicle computer. When the vehicle has been loaded with timber the operator activates Path Tracking mode, which means that the vehicle autonomously drives along the recorded path to the transportation road. A new path-tracking algorithm is introduced, and is demonstrated as superior to standard algorithms, such as Follow the Carrot and Pure Pursuit. This is accomplished by using the recorded data from the path-learning phase. By using the recorded steering angle, the curvature of the path is automatically included in the final steering command. Localization is accomplished by fusing data from Real-Time Kinematic Differential GPS/GLONASS, gyro, wheel odometry, and laser odometry. The laser odometry algorithm works by using consecutive scans to estimate the pose change (position and heading). A search is conducted in pose space to find the optimal fit between the two scans. Test results for path tracking and localization accuracy from runs conducted on the full-sized forest machine are presented.

  • 20.
    Lindroos, Ola
    et al.
    SLU.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Pedro, La Hera
    SLU.
    Hohnloser, Peter
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Estimating the position of the harvester head: a key step towards the precision forestry of the future?2015Ingår i: Croatian Journal of Forest Engineering, ISSN 1845-5719, E-ISSN 1848-9672, Vol. 36, nr 2, s. 147-164Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Modern harvesters are technologically sophisticated, with many useful features such as the ability to automatically measure stem diameters and lengths. This information is processed in real time to support value optimization when cutting stems into logs. It can also be transferred from the harvesters to centralized systems and used for wood supply management. Such information management systems have been available since the 1990s in Sweden and Finland, and are constantly being upgraded. However, data on the position of the harvester head relative to the machine are generally not recorded during harvesting. The routine acquisition and analysis of such data could offer several opportunities to improve forestry operations and related processes in the future. Here, we analyze the possible benefits of having this information, as well as the steps required to collect and process it. The benefits and drawbacks of different sensing technologies are discussed in terms of potential applications, accuracy and cost. We also present the results of preliminary testing using two of the proposed methods. Our analysis indicates that an improved scope for mapping and controlling machine movement is the main benefit that is directly related to the conduct of forestry operations. In addition, there are important indirect benefits relating to ecological mapping. Our analysis suggests that both of these benefits can be realized by measuring the angles of crane joints or the locations of crane segments and using the resulting information to compute the head's position. In keeping with our findings, two companies have recently introduced sensor equipped crane solutions.

  • 21.
    Ostovar, Ahmad
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Human Detection Based on Infrared Images in Forestry Environments2016Ingår i: Image Analysis and Recognition (ICIAR 2016): 13th International Conference, ICIAR 2016, in Memory of Mohamed Kamel, Póvoa de Varzim, Portugal, July 13-15, 2016, Proceedings, 2016, s. 175-182Konferensbidrag (Refereegranskat)
    Abstract [en]

    It is essential to have a reliable system to detect humans in close range of forestry machines to stop cutting or carrying operations to prohibit any harm to humans. Due to the lighting conditions and high occlusion from the vegetation, human detection using RGB cameras is difficult. This paper introduces two human detection methods in forestry environments using a thermal camera; one shape-dependent and one shape-independent approach. Our segmentation algorithm estimates location of the human by extracting vertical and horizontal borders of regions of interest (ROIs). Based on segmentation results, features such as ratio of height to width and location of the hottest spot are extracted for the shape-dependent method. For the shape-independent method all extracted ROI are resized to the same size, then the pixel values (temperatures) are used as a set of features. The features from both methods are fed into different classifiers and the results are evaluated using side-accuracy and side-efficiency. The results show that by using shape-independent features, based on three consecutive frames, we reach a precision rate of 80 % and recall of 76 %.

  • 22.
    Ostovar, Ahmad
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Adaptive Image Thresholding of Yellow Peppers for a Harvesting Robot2018Ingår i: Robotics, E-ISSN 2218-6581, Vol. 7, nr 1, artikel-id 11Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The presented work is part of the H2020 project SWEEPER with the overall goal to develop a sweet pepper harvesting robot for use in greenhouses. As part of the solution, visual servoing is used to direct the manipulator towards the fruit. This requires accurate and stable fruit detection based on video images. To segment an image into background and foreground, thresholding techniques are commonly used. The varying illumination conditions in the unstructured greenhouse environment often cause shadows and overexposure. Furthermore, the color of the fruits to be harvested varies over the season. All this makes it sub-optimal to use fixed pre-selected thresholds. In this paper we suggest an adaptive image-dependent thresholding method. A variant of reinforcement learning (RL) is used with a reward function that computes the similarity between the segmented image and the labeled image to give feedback for action selection. The RL-based approach requires less computational resources than exhaustive search, which is used as a benchmark, and results in higher performance compared to a Lipschitzian based optimization approach. The proposed method also requires fewer labeled images compared to other methods. Several exploration-exploitation strategies are compared, and the results indicate that the Decaying Epsilon-Greedy algorithm gives highest performance for this task. The highest performance with the Epsilon-Greedy algorithm ( ϵ = 0.7) reached 87% of the performance achieved by exhaustive search, with 50% fewer iterations than the benchmark. The performance increased to 91.5% using Decaying Epsilon-Greedy algorithm, with 73% less number of iterations than the benchmark.

  • 23.
    Ostovar, Ahmad
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Division of Forestry and Forest Resources, Norwegian Institute of Bioeconomy Research (NIBIO), P.O. Box 115, 1431 Ås, Norway.
    Talbot, Bruce
    Puliti, Stefano
    Astrup, Rasmus
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Detection and classification of Root and Butt-Rot (RBR) in Stumps of Norway Spruce Using RGB Images and Machine Learning2019Ingår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, nr 7, artikel-id 1579Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Root and butt-rot (RBR) has a significant impact on both the material and economic outcome of timber harvesting, and therewith on the individual forest owner and collectively on the forest and wood processing industries. An accurate recording of the presence of RBR during timber harvesting would enable a mapping of the location and extent of the problem, providing a basis for evaluating spread in a climate anticipated to enhance pathogenic growth in the future. Therefore, a system to automatically identify and detect the presence of RBR would constitute an important contribution to addressing the problem without increasing workload complexity for the machine operator. In this study, we developed and evaluated an approach based on RGB images to automatically detect tree stumps and classify them as to the absence or presence of rot. Furthermore, since knowledge of the extent of RBR is valuable in categorizing logs, we also classify stumps into three classes of infestation; rot = 0%, 0% < rot > 50% and rot ≥ 50%. In this work we used deep-learning approaches and conventional machine-learning algorithms for detection and classification tasks. The results showed that tree stumps were detected with precision rate of 95% and recall of 80%. Using only the correct output (TP) of the stump detector, stumps without and with RBR were correctly classified with accuracy of 83.5% and 77.5%, respectively. Classifying rot into three classes resulted in 79.4%, 72.4%, and 74.1% accuracy for stumps with rot = 0%, 0% < rot > 50% and rot ≥ 50%, respectively. With some modifications, the developed algorithm could be used either during the harvesting operation to detect RBR regions on the tree stumps or as an RBR detector for post-harvest assessment of tree stumps and logs.

  • 24.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Automation in forestry: development of unmanned forwarders2011Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [sv]

    De senaste 50 åren har skogsbruket blivit alltmer mekaniserat. I det moderna skogsbruket i Europa används normalt två olika maskiner; en skördare som fäller, kvistar och kapar träden till stockar samt en skotare som transporterar dem till närmsta väg. Dessa maskiner är tekniskt avancerade och ganska dyra, men har samtidigt en mycket hög produktivitet. De är så effektiva att föraren riskerar att bli en flaskhals om produktiviteten ökar ännu mer. Ett sätt att lösa detta är att ändra arbetssätt så att ett eller flera arbetsmoment inte behövs längre. Därmed ökar effektiviteten utan att arbetsbördan ökar. Ett annat sätt att lösa problemet är att utveckla (halv-)autonoma fordon. En del av denna avhandling är en analys av ekonomisk prestanda för fyra tänkbara system som alla bygger på konceptet integrerad lastning, varav två använder autonoma skotare. Resultaten visar att ett lovande system är ett lastväxlingssystem där en autonom skotare byter lastutrymme med en bemannad drivare, en kombination av skotare och skördare. Autonoma skotare som kan utföra samma arbete som konventionella skotare visade sig ha störst potential av de analyserade systemen.Tekniker och algoritmer för autonom navigering av skotare för transport av stockar till närmaste väg är en viktig del i avhandlingen. En ny algoritm för att följa en tidigare demonstrerad väg med hög noggrannhet introduceras. För att undvika hinder modifierades algoritmen VFH+ så att den fungerar med skogsmaskiner. Tester med en skotare visade emellertid att algoritmen presterar otillfredsställande i trånga passager med näraliggande hinder på båda sidor av fordonet. Detta ledde till utvecklingen av en algoritm för ruttplanering för terränggående fordon som med hjälp av en simulator kan förutsäga kollisioner i ett fönster framåt i tiden. Ruttplaneraren klarar att navigera en skogsmaskin förbi hinder som finns på eller nära rutten på ett sätt som är svårt eller omöjligt att uppnå med standardalgoritmer för att undvika hinder, eftersom de inte beaktar formen på fordonet.För att kunna hantera en mångfald av sensorer, styrdon och annan hårdvara på ett systematiskt och enhetligt sätt, och för att möjliggöra för kommunikation mellan mjukvarumoduler, implementerades ett programvarusystem (ofta kallat middleware). Systemet kan distribueras över ett nätverk av datorer om några programmoduler kräver mer datorkraft. Detta ramverk har visat sig vara ett kraftfullt verktyg för forskning och utveckling av autonoma fordon. Ett vanligt problem i skogsbruket är hjulslirning som orsakar markskador och minskar framkomligheten för skogsmaskiner. Med hjälp av data som samlats in under experimenten med den autonoma skogsmaskinen utvecklades en metod för att mäta hjulslirning. Denna metod kan användas för att upptäcka slirning mellan hjul och mark och skulle kunna användas för att styra maskinens transmission för att minska slirning.

  • 25.
    Ringdahl, Ola
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Techniques and Algorithms for Autonomous Vehicles in Forest Environment2007Licentiatavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    This thesis describes an ongoing project of which the purpose is designing and developing techniques and algorithms for autonomous off-road vehicles. The focus is on some of the components necessary to accomplish autonomous navigation, which involves sensing and moving safely along a user-defined path in a dynamic forest environment. The work is part of a long-term vision in the forest industry of developing an unmanned shuttle that transports timber from the felling area to the main roads for further transportation. A new path-tracking algorithm is introduced and demonstrated as superior to standard algorithms, such as Follow the Carrot and Pure Pursuit. This is accomplished by using recorded data from a path-learning phase. By using the recorded steering angle, the curvature of the path is automatically included in the final steering command. Localization is accomplished by a neural network that fuses data from a Real-Time Kinematic Differential GPS/GLONASS, a gyro, and wheel odometry. Test results are presented for path tracking and localization accuracy from runs conducted on a full-sized forest machine. A large part of the work has been design and implementation of a general software platform for research in autonomous vehicles. The developed algorithms and software have been implemented and tested on a full-size forest machine supplied by our industrial partner Komatsu Forest AB. Results from successful field tests with autonomous path tracking, including obstacle avoidance, are presented.

  • 26.
    Ringdahl, Ola
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Autonomous Forest Machines: Techniques and Algorithms for Unmanned Vehicles2008Bok (Övrigt vetenskapligt)
    Abstract [en]

    With continued development of forest machines the operators risk becoming a bottleneck, due to the ever increasing pace they have to work in. Different kind of aids for the operators will become necessary to lessen the workload. Development of autonomous forest machines aims at meeting this demand. This book describes an ongoing project of which the purpose is designing and developing techniques and algorithms for such a vehicle. The focus is on some of the components necessary to accomplish autonomous navigation, which involves sensing and moving safely along a user-defined path in a dynamic forest environment. A new path-tracking algorithm is introduced and demonstrated as superior to standard algorithms, such as Follow the Carrot and Pure Pursuit. Localization is accomplished by a neural network that fuses data from a GPS, a gyro, and wheel odometry. Results from successful field tests on a full-size forest machine with autonomous path tracking, including obstacle avoidance, are presented. The book will be of interest to students and researchers in the area of autonomous vehicles and artificial intelligence.

  • 27.
    Ringdahl, Ola
    et al.
    Umeå universitet.
    Hellström, Thomas
    Umeå universitet.
    Autonomous Navigation in Forest Environment2006Ingår i: Proceedings from the 23rd Anual workshop of the Swedish Artificial Intelligence Society (SAIS06),, 2006Konferensbidrag (Övrigt vetenskapligt)
  • 28.
    Ringdahl, Ola
    et al.
    Umeå universitet.
    Hellström, Thomas
    Umeå universitet.
    Follow the Past - A Path Tracking Method Using Recorded Orientation and Steering Commands.2005Ingår i: Proceedings of The Third Swedish Workshop on Autonomous Robotics (SWAR05), 2005Konferensbidrag (Övrig (populärvetenskap, debatt, mm))
  • 29.
    Ringdahl, Ola
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Lindroos, Ola
    Dept. of Forest Resource Management, Swedish University of Agricultural Sciences.
    Potentials of possible machine systems for directly loading logs in cut-to-length harvesting2012Ingår i: Canadian Journal of Forest Research, ISSN 0045-5067, E-ISSN 1208-6037, Vol. 42, nr 5, s. 970-985Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In conventional mechanized cut-to-length systems, a harvester fells and cuts trees into logs that are stored on the ground until a forwarder picks them up and carries them to landing sites. A proposed improvement is to place logs directly into the load spaces of transporting machines as they are cut. Such integrated loading could result in cost reductions, shorter lead times from stump to landing, and lower fuel consumption. However, it might also create waiting times for the machines involved, whereas multifunctional machines are likely to be expensive. Thus, it is important to analyze whether or not the advantages of any changes outweigh the disadvantages. The conventional system was compared with four potential systems, including two with autonomous forwarders, using discrete-event simulation with stochastic elements in which harvests of more than 1000 final felling stands (containing in total 1.6 million m3) were simulated 35 times per system. The results indicate that harwarders have substantial potential (less expensive on ≥80% of the volume and fuel consumption decreased by ≥18%) and may become competitive if key innovations are developed. Systems with cooperating machines have considerably less potential, limited to very specific stand conditions. The results conform with expected difficulties in integrating processing and transporting machines’ work in variable environments.

  • 30.
    Ringdahl, Ola
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Wästerlund, Iwan
    Dept. of Forest Resource Management, Swedish University of Agricultural Sciences.
    Lindroos, Ola
    Dept. of Forest Resource Management, Swedish University of Agricultural Sciences.
    Estimating wheel slip for a forest machine using RTK-DGPS2012Ingår i: Journal of terramechanics, ISSN 0022-4898, E-ISSN 1879-1204, Vol. 49, nr 5, s. 271-279Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Wheel slip may increase the risk for wheel rutting and tear up ground vegetation and superficial roots and thereby decreasing the bearing capacity of the ground, but also reducing the growth of nearby standing forest trees. With increased slip, more energy is consumed for making wheel ruts in the ground, with increased fuel consumption as a result. This paper proposes a novel method for measuring slip in an uneven forest terrain with an 8WD forestry machine. This is done by comparing the wheel velocity reported by the machine and velocity measured with an accurate DGPS system. Field tests with a forestry machine showed that slip could be calculated accurately with the suggested method. The tests showed that there was almost no slip on asphalt or gravel surfaces. In a forest environment, 10–15% slip was common. A future extension of the method enabling estimation of the slip of each wheel pair in the bogies is also suggested.

  • 31.
    Ringdahl, Ola
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hohnloser, Peter
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Holmgren, Johan
    Dept. of Forest Resource Management, Swedish University of Agricultural Sciences.
    Lindroos, Ola
    Department of Forest Biomaterials and Technology, Swedish University of Agricultural Sciences.
    Enhanced Algorithms for Estimating Tree Trunk Diameter Using 2D Laser Scanner2013Ingår i: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 5, nr 10, s. 4839-4856Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Accurate vehicle localization in forest environments is still an unresolved problem. Global navigation satellite systems (GNSS) have well known limitations in dense forest, and have to be combined with for instance laser based SLAM algorithms to provide satisfying accuracy. Such algorithms typically require accurate detection of trees, and estimation of tree center locations in laser data. Both these operations depend on accurate estimations of tree trunk diameter. Diameter estimations are important also for several other forestry automation and remote sensing applications. This paper evaluates several existing algorithms for diameter estimation using 2D laser scanner data. Enhanced algorithms, compensating for beam width and using multiple scans, were also developed and evaluated. The best existing algorithms overestimated tree trunk diameter by ca. 40%. Our enhanced algorithms, compensating for laser beam width, reduced this error to less than 12%.

  • 32.
    Ringdahl, Ola
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Kurtser, Polina
    Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel.
    Barth, Ruud
    Greenhouse Horticulture, Wageningen University and Research Centre, Wageningen, the Netherlands.
    Edan, Yael
    Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel .
    Operational flow of an autonomous sweetpepper harvesting robot2016Konferensbidrag (Refereegranskat)
    Abstract [en]

    Advanced automation is required for greenhouse production systems due to the lack of skilled workforce and increasing labour costs [1]. As part of the EU project SWEEPER, we are working on developing an autonomous robot able to harvest sweet pepper fruits in greenhouses. This paper focuses on the operational flow of the robot for the high level task planning.

    In the SWEEPER project, an RGB camera is mounted on the end effector to detect fruits. Due to the dense plant rows, the camera is located at a maximum of 40 cm from the plants and hence cannot provide an overview of all fruit locations. Only a few ripe fruits at each acquisition can be seen. This implies that the robot must incorporate a search pattern to look for fruits. When at least one fruit has been detected in the image, the search is aborted and a harvesting phase is initiated. The phase starts with directing the manipulator to a point close to the fruit and then activating a visual servo control loop. This motion approach ensures that the fruit is grasped despite the occlusions caused by the stems and leaves. When the manipulator has reached the fruit, it is harvested and automatically released into a container. If there are more fruits that have already been detected, the system continues to pick them. When all detected fruits have been harvested, the system resumes the search pattern again. When the search pattern is finished and no more fruits are detected, the robot base is advanced along the row to the next plant and repeats the operations above.

    To support implementation of the workflow into a program controlling the actual robot, a generic software framework for development of agricultural and forestry robots was used [2]. The framework is constructed with a hybrid robot architecture, using a state machine implementing the following flowchart.

  • 33.
    Ringdahl, Ola
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Kurtser, Polina
    Edan, Yael
    Performance of RGB-D camera for different object types in greenhouse conditions2019Ingår i: 2019 European Conference on Mobile Robots (ECMR) / [ed] Libor Přeučil, Sven Behnke, Miroslav Kulich, IEEE, 2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    RGB-D cameras play an increasingly important role in localization and autonomous navigation of mobile robots. Reasonably priced commercial RGB-D cameras have recently been developed for operation in greenhouse and outdoor conditions. They can be employed for different agricultural and horticultural operations such as harvesting, weeding, pruning and phenotyping. However, the depth information extracted from the cameras varies significantly between objects and sensing conditions. This paper presents an evaluation protocol applied to a commercially available Fotonic F80 time-of-flight RGB-D camera for eight different object types. A case study of autonomous sweet pepper harvesting was used as an exemplary agricultural task. Each of the objects chosen is a possible item that an autonomous agricultural robot must detect and localize to perform well. A total of 340 rectangular regions of interests (ROI) were marked for the extraction of performance measures of point cloud density, and variability around center of mass, 30-100 ROIs per object type. An additional 570 ROIs were generated (57 manually and 513 replicated) to evaluate the repeatability and accuracy of the point cloud. A statistical analysis was performed to evaluate the significance of differences between object types. The results show that different objects have significantly different point density. Specifically metallic materials and black colored objects had significantly less point density compared to organic and other artificial materials introduced to the scene as expected. The point cloud variability measures showed no significant differences between object types, except for the metallic knife that presented significant outliers in collected measures. The accuracy and repeatability analysis showed that 1-3 cm errors are due to the the difficulty for a human to annotate the exact same area and up to ±4 cm error is due to the sensor not generating the exact same point cloud when sensing a fixed object.

  • 34.
    Ringdahl, Ola
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Kurtser, Polina
    Edan, Yael
    Strategies for selecting best approach direction for a sweet-pepper harvesting robot2017Ingår i: Towards Autonomous Robotic Systems: 18th Annual Conference, TAROS 2017, Guildford, UK, July 19–21, 2017, Proceedings / [ed] Yang Gao, Saber Fallah, Yaochu Jin, Constantina Lekakou, Cham: Springer, 2017, s. 516-525Konferensbidrag (Refereegranskat)
    Abstract [en]

    An autonomous sweet pepper harvesting robot must perform several tasks to successfully harvest a fruit. Due to the highly unstructured environment in which the robot operates and the presence of occlusions, the current challenges are to improve the detection rate and lower the risk of losing sight of the fruit while approaching the fruit for harvest. Therefore, it is crucial to choose the best approach direction with least occlusion from obstacles.

    The value of ideal information regarding the best approach direction was evaluated by comparing it to a method attempting several directions until successful harvesting is performed. A laboratory experiment was conducted on artificial sweet pepper plants using a system based on eye-in-hand configuration comprising a 6DOF robotic manipulator equipped with an RGB camera. The performance is evaluated in laboratorial conditions using both descriptive statistics of the average harvesting times and harvesting success as well as regression models. The results show roughly 40–45% increase in average harvest time when no a-priori information of the correct harvesting direction is available with a nearly linear increase in overall harvesting time for each failed harvesting attempt. The variability of the harvesting times grows with the number of approaches required, causing lower ability to predict them.

    Tests show that occlusion of the front of the peppers significantly impacts the harvesting times. The major reason for this is the limited workspace of the robot often making the paths to positions to the side of the peppers significantly longer than to positions in front of the fruit which is more open.

  • 35.
    Ringdahl, Ola
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Lindroos, Ola
    Dept. of Forest Resource Management, Swedish University of Agricultural Sciences.
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Bergström, Dan
    Athanassiadis, Dimitris
    Dept. of Forest Resource Management, Swedish University of Agricultural Sciences.
    Nordfjell, Tomas
    Dept. of Forest Resource Management, Swedish University of Agricultural Sciences.
    Path tracking in forest terrain by an autonomous forwarder2011Ingår i: Scandinavian Journal of Forest Research, ISSN 0282-7581, E-ISSN 1651-1891, Vol. 26, nr 4, s. 350-359Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Autonomous navigation in forest terrain, where operation paths are rarely straight or flat and obstacles are common, is challenging. This paper evaluates a system designed to autonomously follow previously demonstrated paths in a forest environment without loading/unloading timber, a pre-step in the development of fully autonomous forwarders. The system consisted of a forwarder equipped with a high-precision global positioning system to measure the vehicle’s heading and position. A gyro was used to compensate for the influence of the vehicle’s roll and pitch. On an ordinary clear-cut forest area with numerous stumps, the vehicle was able to follow two different tracks, three times each at a speed of 1 m s-1, with a mean path tracking error of 6 and 7 cm, respectively. The error never exceeded 35 cm, and in 90% of the observations it was less than 14 and 15 cm, respectively. This accuracy is well within the necessary tolerance for forestry operations. In fact, a human operator would probably have a hard time following the track more accurately. Hence, the developed systems function satisfactorily when using previously demonstrated paths. However, further research on planning new paths in unknown unstructured terrain and on loading/unloading is required before timber transports can be fully automated.

  • 36.
    Ringdahl, Ola
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ostovar, Ahmad
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Division of Forestry and Forest Resources, Norwegian Institute of Bioeconomy Research (NIBIO), P.O. Box 115, 1431 Ås, Norway.
    Talbot, Bruce
    Division of Forestry and Forest Resources, Norwegian Institute of Bioeconomy Research (NIBIO).
    Puliti, Stefano
    Division of Forestry and Forest Resources, Norwegian Institute of Bioeconomy Research (NIBIO).
    Rasmus, Astrup
    Division of Forestry and Forest Resources, Norwegian Institute of Bioeconomy Research (NIBIO).
    Using RGB images and machine learning to detect and classify Root and Butt-Rot (RBR) in stumps of Norway spruce2019Ingår i: Forest Operations in Response to Environmental Challenges, 2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    Root and butt-rot (RBR) has a significant impact on both the material and economic outcome of timber harvesting. An accurate recording of the presence of RBR during timber harvesting would enable a mapping of the location and extent of the problem, providing a basis for evaluating spread in a climate anticipated to enhance pathogenic growth in the future. Therefore, a system to automatically identify and detect the presence of RBR would constitute an important contribution in addressing the problem without increasing workload complexity for the machine operator. In this study we developed and evaluated an approach based on RGB images to automatically detect tree-stumps and classify them as to the absence or presence of rot. Furthermore, since knowledge of the extent of RBR is valuable in categorizing logs, we also classify stumps to three classes of infestation; rot = 0%, 0% < rot < 50% and rot ≥50%. We used deep learning approaches and conventional machine learning algorithms for detection and classification tasks. The results showed that tree-stumps were detected with precision rate of 95% and recall of 80%. Stumps without and with root and butt-rot were correctly classified with accuracy of 83.5% and 77.5%. Classifying rot into three classes resulted in 79.4%, 72.4% and 74.1% accuracy respectively. With some modifications, the algorithm developed could be used either during the harvesting operation to detect RBR regions on the tree-stumps or as a RBR detector for post-harvest assessment of tree-stumps and logs.

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