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. © 2011 Springer-Verlag.
CITATION STYLE
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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7102 LNAI, pp. 525–535). https://doi.org/10.1007/978-3-642-25489-5_51
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