Vision Based Collision Avoidance For Multi-Agent Systems Using Avoidance Functions

In this paper, a methodology for designing control strategies that guarantee collision avoidance for multi-agent systems without the information about the relative distances among the agents, is provided. The controllers are designed using avoidance functions that rely only on the visual information, that is, times-to-collision and line-of-sight angle. This method is particularly suitable to low-cost and/or small robotic systems that are not equipped with range measurement devices like radars and lidars. Finally, the collision avoidance is guaranteed using Lyapunov analysis type of technical arguments and illustrated using simulations.

[1]  Zhiyong Chen,et al.  Design of Obstacle Avoidance System for Micro-UAV Based on Binocular Vision , 2017, 2017 International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII).

[2]  Thomas P. Spriesterbach,et al.  Unmanned Aircraft System Airspace Integration in the National Airspace Using a Ground-Based Sense and Avoid System , 2013 .

[3]  Nathan Michael,et al.  Vision-Based, Distributed Control Laws for Motion Coordination of Nonholonomic Robots , 2009, IEEE Transactions on Robotics.

[4]  Sebastian Scherer,et al.  First results in detecting and avoiding frontal obstacles from a monocular camera for micro unmanned aerial vehicles , 2013, 2013 IEEE International Conference on Robotics and Automation.

[5]  Randal W. Beard,et al.  Reactive Path Planning for Micro Air Vehicles Using Bearing-only Measurements , 2011, Journal of Intelligent & Robotic Systems.

[6]  Jason J. Ford,et al.  Vision-based detection and tracking of aerial targets for UAV collision avoidance , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Antonio Marín-Hernández,et al.  Decision making for obstacle avoidance in autonomous mobile robots by time to contact and optical flow , 2015, 2015 International Conference on Electronics, Communications and Computers (CONIELECOMP).

[8]  George Leitmann,et al.  Evasion in the plane , 1978 .

[9]  Thiago Marinho Bio-inspired vision-based evasion control: collision avoidance without distance measurement , 2019 .

[10]  Naira Hovakimyan,et al.  Guaranteed Collision Avoidance Based on Line-of-Sight Angle and Time-to-Collision , 2018, 2018 Annual American Control Conference (ACC).

[11]  Li Rui,et al.  Obstacle avoidance for outdoor flight of a quadrotor based on computer vision , 2017, 2017 29th Chinese Control And Decision Conference (CCDC).

[12]  Amaury Nègre,et al.  Real-Time Time-to-Collision from Variation of Intrinsic Scale , 2006, ISER.

[13]  Vijay Kumar,et al.  Bearing-only formation control with auxiliary distance measurements, leaders, and collision avoidance , 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

[14]  Mark W. Spong,et al.  Cooperative Avoidance Control for Multiagent Systems , 2007 .

[15]  Amaury Nègre,et al.  A comparison of three methods for measure of Time to Contact , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  G. Leitmann,et al.  Avoidance control , 1977 .

[17]  James J. Gibson,et al.  The Ecological Approach to Visual Perception: Classic Edition , 2014 .

[18]  Li Jie,et al.  Expansion rate based collision avoidance for Unmanned Aerial Vehicles , 2015, 2015 34th Chinese Control Conference (CCC).

[19]  Holger Voos UAV see and avoid with nonlinear filtering and non-cooperative avoidance , 2007 .

[20]  Naira Hovakimyan,et al.  Collision Avoidance Based on Line-of-Sight Angle , 2018, J. Intell. Robotic Syst..

[21]  Kazuyuki Ito,et al.  Determination of time to contact and application to timing control of mobile robot , 2010, 2010 IEEE International Conference on Robotics and Biomimetics.

[22]  Lawrence M. Dill,et al.  The escape response of the zebra danio (Brachydanio rerio) I. The stimulus for escape , 1974 .

[23]  Daniel Raviv,et al.  Autonomous obstacle avoidance using visual fixation and looming , 1992, Other Conferences.

[24]  Shane C. Degen Reactive image-based collision avoidance system for unmanned aircraft systems , 2011 .

[25]  Ryan M. Eustice,et al.  Visual localization within LIDAR maps for automated urban driving , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[26]  Naira Hovakimyan,et al.  Cooperative Path Following of Multiple Multirotors Over Time-Varying Networks , 2015, IEEE Transactions on Automation Science and Engineering.