Abstract
Multi-link wheeled robots provide interesting opportunities within many areas such as inspection and maintenance of pipes or vents. A key functionality in order to perform such operations, is that the robot can follow a predefined path fast and accurately. In this paper we present an algorithm to learn the path-following behavior for a set of motion primitives. These primitives could then be used by a planner in order to construct longer paths. The algorithm is divided into two steps: an example-based stage for controller learning, and a controller tuning stage, based on an objective function and simulations of the path-following process. The path-following controllers have been tested with a simulator of a multi-link robot in several complex paths, showing an excellent performance.
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Marín, F.J., Casillas, J., Mucientes, M., Transeth, A.A., Fjerdingen, S.A., Schjølberg, I. (2011). Learning Intelligent Controllers for Path-Following Skills on Snake-Like Robots. In: Jeschke, S., Liu, H., Schilberg, D. (eds) Intelligent Robotics and Applications. ICIRA 2011. Lecture Notes in Computer Science(), vol 7102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25489-5_51
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DOI: https://doi.org/10.1007/978-3-642-25489-5_51
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