ICRA 2012 Paper Abstract


Paper TuA09.4

van den Berg, Jur (University of Utah), Wilkie, David (University of North Carolina), Guy, Stephen J. (Univ. of North Carolina at Chapel Hill), Niethammer, Marc (UNC Chapel Hill), Manocha, Dinesh (UNC at Chapel Hill)

LQG-Obstacles: Feedback Control with Collision Avoidance for Mobile Robots with Motion and Sensing Uncertainty

Scheduled for presentation during the Regular Session "Collision" (TuA09), Tuesday, May 15, 2012, 09:15−09:30, Meeting Room 9 (Sa)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on November 14, 2018

Keywords Collision Avoidance, Motion and Path Planning, Robust/Adaptive Control of Robotic Systems


This paper presents LQG-Obstacles, a new concept that combines linear-quadratic feedback control of mobile robots with guaranteed avoidance of collisions with obstacles. Our approach generalizes the concept of Velocity Obstacles to any robotic system with a linear Gaussian dynamics model. We integrate a Kalman filter for state estimation and an LQR feedback controller into a closed-loop dynamics model of which a higher-level control objective is the ``control input''. We then define the LQG-Obstacle as the set of control objectives that result in a collision with high probability. Selecting a control objective outside the LQG-Obstacle then produces collision-free motion. We demonstrate the potential of LQG-Obstacles by safely and smoothly navigating a simulated quadrotor helicopter with complex non-linear dynamics and motion and sensing uncertainty through three-dimensional environments with obstacles and narrow passages.



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