Claassens, J2010-07-122010-07-122010Claassens, J. An RRT-Based path planner for use in trajectory imitation. 2010. IEEE International Conference on Robotics and Automation. Anchorage, Alaska, 3-8 May 2010, pp 6http://hdl.handle.net/10204/4058IEEE International Conference on Robotics and Automation. Anchorage, Alaska, 3-8 May 2010The authors propose a more robust robot programming; by demonstration system planner that produces a reproduction; path which satisfies statistical constraints derived from demonstration; trajectories and avoids obstacles given the freedom; in those constraints. To determine the statistical constraints a; Gaussian Mixture Model is fitted to demonstration trajectories.; These demonstrations are recorded through kinesthetic; teaching of a redundant manipulator. The GMM models the; likelihood of configurations given time. The planner is based; on Rapidly-exploring Random Tree search with the search tree; kept within the statistical model. Collision avoidance is included; by not allowing the tree to grow into obstacles. The system is; designed to act as a backup for if a faster reactive planner falls; within a local minima.; To illustrate its performance an experiment is conducted; where the system is taught to open a Pelican case using a; Barrett Whole Arm Manipulator (WAM). During reproduction; an obstacle is placed nearby the case to partially obstruct; the manipulator. The planner successfully avoided this obstacle; without drifting from the trends in the demonstrationsenManipulator planningImitationTrajectoriesConference PresentationClaassens, J. (2010). An RRT-Based path planner for use in trajectory imitation. IEEE. http://hdl.handle.net/10204/4058Claassens, J. "An RRT-Based path planner for use in trajectory imitation." (2010): http://hdl.handle.net/10204/4058Claassens J, An RRT-Based path planner for use in trajectory imitation; IEEE; 2010. http://hdl.handle.net/10204/4058 .TY - Conference Presentation AU - Claassens, J AB - The authors propose a more robust robot programming; by demonstration system planner that produces a reproduction; path which satisfies statistical constraints derived from demonstration; trajectories and avoids obstacles given the freedom; in those constraints. To determine the statistical constraints a; Gaussian Mixture Model is fitted to demonstration trajectories.; These demonstrations are recorded through kinesthetic; teaching of a redundant manipulator. The GMM models the; likelihood of configurations given time. The planner is based; on Rapidly-exploring Random Tree search with the search tree; kept within the statistical model. Collision avoidance is included; by not allowing the tree to grow into obstacles. The system is; designed to act as a backup for if a faster reactive planner falls; within a local minima.; To illustrate its performance an experiment is conducted; where the system is taught to open a Pelican case using a; Barrett Whole Arm Manipulator (WAM). During reproduction; an obstacle is placed nearby the case to partially obstruct; the manipulator. The planner successfully avoided this obstacle; without drifting from the trends in the demonstrations DA - 2010 DB - ResearchSpace DP - CSIR KW - Manipulator planning KW - Imitation KW - Trajectories LK - https://researchspace.csir.co.za PY - 2010 T1 - An RRT-Based path planner for use in trajectory imitation TI - An RRT-Based path planner for use in trajectory imitation UR - http://hdl.handle.net/10204/4058 ER -