Motion planning for persistent traveling solar-powered unmanned ground vehicles

This paper examines a mission planning problem for a solar-powered unmanned ground vehicle (UGV) which requires the vehicle to visit a series of objective points in minimal time subject to a strict net-energy change constraint. Though related to the Traveling Salesperson Problem, the mission planning problem discussed herein imposes further complexity through additional coupled mixed-variable sets and the strict energy constraint. A scalar field representing the solar radiation of the mission environment is first characterized from a visual-spectrum image. A cascaded particle swarm optimization algorithm, coupled with the integer linear programming technique, is used to generate a time-optimized motion plan and power schedules for the UGV, which guides it to visit the assigned objective points with optimized sequence and paths, and then return to its starting location and orientation while guaranteeing compliance with the net energy gain constraint.

[1]  Y. Charlie Hu,et al.  Energy-efficient motion planning for mobile robots , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[2]  Pratap Tokekar,et al.  Energy-Efficient Path Planning for Solar-Powered Mobile Robots , 2012, ISER.

[3]  B. Faverjon,et al.  Probabilistic Roadmaps for Path Planning in High-Dimensional Con(cid:12)guration Spaces , 1996 .

[4]  Richard L. Church,et al.  Finding shortest paths on real road networks: the case for A* , 2009, Int. J. Geogr. Inf. Sci..

[5]  Emilio Frazzoli,et al.  Sampling-based algorithms for optimal motion planning , 2011, Int. J. Robotics Res..

[6]  Jonathan P. How,et al.  An Automated Battery Management System to Enable Persistent Missions With Multiple Aerial Vehicles , 2015, IEEE/ASME Transactions on Mechatronics.

[7]  Devin J. Balkcom,et al.  Time Optimal Trajectories for Bounded Velocity Differential Drive Vehicles , 2002, Int. J. Robotics Res..

[8]  Nicholas R. J. Lawrance,et al.  Autonomous Exploration of a Wind Field with a Gliding Aircraft , 2011 .

[9]  Lydia E. Kavraki,et al.  Probabilistic roadmaps for path planning in high-dimensional configuration spaces , 1996, IEEE Trans. Robotics Autom..

[10]  R. A. Zemlin,et al.  Integer Programming Formulation of Traveling Salesman Problems , 1960, JACM.

[11]  Meng Wang,et al.  Staying-alive and energy-efficient path planning for mobile robots , 2008, 2008 American Control Conference.

[12]  Ran Dai,et al.  Integrated path planning and power management for solar-powered unmanned ground vehicles , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[13]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[14]  O. Weck,et al.  A COMPARISON OF PARTICLE SWARM OPTIMIZATION AND THE GENETIC ALGORITHM , 2005 .

[15]  Mehran Mesbahi,et al.  Trajectory Design and Coverage Control for Solar-Powered UAVs , 2015 .

[16]  Jonathan P. How,et al.  Mission Health Management for 24/7 Persistent Surveillance Operations , 2007 .

[17]  Francesco Mondada,et al.  The Autonomous Photovoltaic MarXbot , 2012, IAS.

[18]  Nikhil Nigam,et al.  The Multiple Unmanned Air Vehicle Persistent Surveillance Problem: A Review , 2014 .

[19]  B. Bethke,et al.  Group health management of UAV teams with applications to persistent surveillance , 2008, 2008 American Control Conference.