A static obstacle collision mitigation control scheme for flexible formation of nonholonomic mobile robots, with experiments

In this paper, a static obstacle collision mitigation scheme is proposed for flexible formation of nonholonomic mobile robots. The aim of the collision mitigation scheme is to prevent a flexible formation of mobile robots from colliding with online detected static obstacles or to decrease the kinetic energy of the collision through coordinated formation braking. The key thrust of the proposed control scheme is that the scheme is able to guarantee a formation braking solution that prevents a formation of mobile robots from colliding with the detected static obstacles under some practically feasible assumptions. The control scheme is based on an online obstacle collision detection module and a formation braking module equipped on each robot to perform the obstacle collision mitigation. The scheme was validated in numerical simulations and partial experiments were conducted for proof-of-concept in some off-road environments at speeds up to 3 m/sec.

[1]  A. Ollero,et al.  Multiple UAV cooperative searching operation using polygon area decomposition and efficient coverage algorithms , 2004, DARS.

[2]  Chang Boon Low,et al.  A dynamic virtual structure formation control for fixed-wing UAVs , 2011, 2011 9th IEEE International Conference on Control and Automation (ICCA).

[3]  Vijay Kumar,et al.  Cooperative Grasping and Transport Using Multiple Quadrotors , 2010, DARS.

[4]  Chang Boon Low,et al.  A flexible virtual structure formation keeping control for fixed-wing UAVs , 2011, 2011 9th IEEE International Conference on Control and Automation (ICCA).

[5]  I. Mas,et al.  Obstacle Avoidance Policies for Cluster Space Control of Nonholonomic Multirobot Systems , 2012, IEEE/ASME Transactions on Mechatronics.

[6]  Vijay Kumar,et al.  Controlling formations of multiple mobile robots , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[7]  Guangming Xie,et al.  Leader-following formation control of multiple mobile vehicles , 2007 .

[8]  Sunil Kumar Agrawal,et al.  Planning and control of UGV formations in a dynamic environment: a practical framework with experiments , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[9]  Chang Boon Low.  Experimental implementation of a novel trajectory tracking control design on a full-sized nonholonomic tracked mobile robot with low-level velocities control systems , 2014, 2014 IEEE Conference on Control Applications (CCA).

[10]  Tim D. Barfoot,et al.  Patch map: A benchmark for occupancy grid algorithm evaluation , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  Chang Boon Low.  A flexible virtual structure formation keeping control design for nonholonomic mobile robots with low-level control systems, with experiments , 2014, 2014 IEEE International Symposium on Intelligent Control (ISIC).

[12]  Farbod Fahimi.  Non-linear model predictive formation control for groups of autonomous surface vessels , 2007, Int. J. Control.

[13]  Franz Andert,et al.  A fast and small 3-D Obstacle model for autonomous applications , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[14]  Maja J. Mataric,et al.  A general algorithm for robot formations using local sensing and minimal communication , 2002, IEEE Trans. Robotics Autom..

[15]  Pedro U. Lima,et al.  Robot formation motion planning using Fast Marching , 2011, Robotics Auton. Syst..

[16]  Danwei Wang,et al.  Real-time distributed optimal trajectory generation for nonholonomic vehicles in formations , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[17]  YangQuan Chen,et al.  Formation control: a review and a new consideration , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Dong Sun,et al.  Coordinated Motion Planning for Multiple Mobile Robots Along Designed Paths With Formation Requirement , 2011, IEEE/ASME Transactions on Mechatronics.

[19]  Tucker R. Balch,et al.  Behavior-based formation control for multirobot teams , 1998, IEEE Trans. Robotics Autom..

[20]  N. DeClaris,et al.  Basic concepts and methods for keeping autonomous ground vehicle formations , 1998, Proceedings of the 1998 IEEE International Symposium on Intelligent Control (ISIC) held jointly with IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA) Intell.

[21]  Q. P. Ha,et al.  Integration of planning and control in robotic formations , 2005 .

[22]  Kar-Han Tan,et al.  High Precision Formation Control of Mobile Robots Using Virtual Structures , 1997, Auton. Robots.

[23]  Ümit Özgüner,et al.  Motion planning for multitarget surveillance with mobile sensor agents , 2005, IEEE Transactions on Robotics.

[24]  Christopher M. Clark,et al.  Motion planning for formations of mobile robots , 2004, Robotics Auton. Syst..

[25]  Chang Boon Low.  A rapid incremental motion planner for flexible formation control of fixed-wing UAVs , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[26]  Ming Xin,et al.  Integrated Optimal Formation Control of Multiple Unmanned Aerial Vehicles , 2012, IEEE Transactions on Control Systems Technology.

[27]  Chang Boon Low,et al.  A trajectory tracking control scheme design for nonholonomic wheeled mobile robots with low-level control systems , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[28]  Xiaoming Hu,et al.  Formation constrained multi-agent control , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).