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Path planning for off-road vehicles with a simulator-in-the-loop
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
2008 (Engelska)Rapport (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.

Ort, förlag, år, upplaga, sidor
Umeå: Datavetenskap , 2008. , s. 20
Serie
Report / UMINF, ISSN 0348-0542 ; 08.07
Nyckelord [en]
Path planning, Autonomous vehicles
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
URN: urn:nbn:se:umu:diva-1771OAI: oai:DiVA.org:umu-1771DiVA, id: diva2:141957
Tillgänglig från: 2008-06-23 Skapad: 2008-06-23 Senast uppdaterad: 2018-06-09Bibliografiskt granskad

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Hellström, ThomasRingdahl, Ola

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