Images taken from slides by B Bayazit G. Dudek. J C Latombe and A. Moore Robot motion planning and (a little) Computational Geometry Transfo Topological Methods Configuration space Skeletonization Potential functions Cell-decomposition Methods Non-holonomic Motion Collision Avoidance Additional reading Latombe, Jean-Claude Robot motion planning. Boston: Kluwer Academic Publishers, 1991 E. Rimon and D. E Koditschek Exact Robot Navigation Using Artificial Potential Functions. IEEE Transactions on Robotics and Automation, 8(5): 501518, October 1992 S. Thrun. Learning metric-topological maps for indoor mobile robot navigation. Artificial Intelligence Ssues Statement Compute a collision-free path for a rigid or articulated object (the robot among static obstacles Inputs Geometry of robot and obstacles Kinematics of robot(degrees of freedom) Initial and goal robot configurations(placements) Output Continuous sequence of collision-free robot configurations connecting the initial and goal configurations Number of degrees of freedom? Holonomic vs Non-holonomic? Kinematic Vs. Kino-dynamic? Planning and control architecture Topological VS Metric? Optimality?Robot Motion Planning and (a little) Computational Geometry Topics: Transforms Topological Methods Configuration space Skeletonization Potential Functions Cell-decomposition Methods Non-holonomic Motion Collision Avoidance Additional reading: Latombe, Jean-Claude. Robot motion planning. Boston : Kluwer Academic Publishers, 1991. E. Rimon and D. E. Koditschek. Exact Robot Navigation Using Artificial Potential Functions. IEEE Transactions on Robotics and Automation, 8(5):501518, October 1992. S. Thrun. Learning metric-topological maps for indoor mobile robot navigation. Artificial Intelligence, 99(1):21-71, 1998. Images taken from slides by B. Bayazit, G. Dudek, J. C. Latombe and A. Moore Issues ● Statement: Compute a collision-free path for a rigid or articulated object (the robot) among static obstacles ● Inputs: – Geometry of robot and obstacles – Kinematics of robot (degrees of freedom) – Initial and goal robot configurations (placements) ● Output: – Continuous sequence of collision-free robot configurations connecting the initial and goal configurations – Number of degrees of freedom? – Holonomic vs. Non-holonomic? – Kinematic vs. Kino-dynamic? – Planning and control architecture – Topological vs. Metric? – Optimality?