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.