IROS 2015 Paper Abstract


Paper ThCT1.4

Bareiss, Daman (University of Utah), van den Berg, Jur (University of Utah), Leang, Kam K. (University of Utah)

Stochastic Automatic Collision Avoidance for Tele-Operated Unmanned Aerial Vehicles

Scheduled for presentation during the Regular session "Collision Detection and Avoidance" (ThCT1), Thursday, October 1, 2015, 12:05−12:20, Saal A1

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sept 28 - Oct 03, 2015, Congress Center Hamburg, Hamburg, Germany

This information is tentative and subject to change. Compiled on July 19, 2019

Keywords Collision Detection and Avoidance, Unmanned Aerial Systems, Telerobotics


This paper presents a stochastic approach for automatic collision avoidance for tele-operated unmanned aerial vehicles (UAVs). Collision detection and mitigation in the presence of uncertainty is an important problem to address because on-board sensing and state estimation uncertainties are inherent in real-world systems. A feedforward-based algorithm is described that continually extrapolates the future trajectory of the vehicle given the current operator control input for collision avoidance. If the predicted probability of a collision is greater than a userdefined confidence bound, the algorithm overrides the operator control input with the nearest, safe command signal to steer the robot away from obstacles, while maintaining user intent. The algorithm is implemented on a simulated quadrotor helicopter (quadcopter) with varying amounts of artificial uncertainty. Simulation results show that for a given confidence bound, the aerial robot is able to avoid collisions, even in a situation where the operator is deliberately attempting to crash the vehicle.



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