A Robust Qualitative Planner for Mobile Robot Navigation Using Human-Provided Maps
A novel method for controlling a mobile robot using qualitative inputs in the context of an approximate map, such as one sketched by a human, is presented. By defining a desired trajectory with respect to observable landmarks, human operators can send semi-autonomous robots into areas for which a truth map is not available. Waypoint planning is formulated as a quadratic optimization problem, resulting in robot trajectories in the true environment that are qualitatively similar to those provided by the human. The algorithm is implemented both in simulation and on a mobile robot platform in several different environments. A sensitivity analysis is performed, illustrating how the method is robust to uncertainties, even large sketch distortions, and allows the robot to adapt and re-plan according to its most current perception of the world.
Danelle C. Shah Mark E. Campbell
Department of Mechanical Engineering,Cornell University,Ithaca,NY
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
2580-2585
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）