Multi-goal path planning algorithm for mobile robots in grid space

In accordance with the problem which ingle target path planning is difficult to simulate the complex real world, this paper presents a new multi-goal path planning method based on grid map for planetary exploration, which designs and realizes the corresponding branch-detected algorithm and heuristic algorithm to solve the local optimal path planning and TSP, eventually reach the target state. The theoretical proof and simulation results show that this algorithm can successfully solve path planning with multi-goal and with a good performance at the same time.

[1]  M. Resende,et al.  A probabilistic heuristic for a computationally difficult set covering problem , 1989 .

[2]  G. Laporte.  The traveling salesman problem: An overview of exact and approximate algorithms , 1992 .

[3]  Anthony Stentz,et al.  The Focussed D* Algorithm for Real-Time Replanning , 1995, IJCAI.

[4]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[5]  Ari K. Jónsson,et al.  MAPGEN: Mixed-Initiative Planning and Scheduling for the Mars Exploration Rover Mission , 2004, IEEE Intell. Syst..

[6]  J.L. Bresina,et al.  Mission operations planning: beyond MAPGEN , 2006, 2nd IEEE International Conference on Space Mission Challenges for Information Technology (SMC-IT'06).

[7]  Philippe Lacomme,et al.  A genetic algorithm for a bi-objective capacitated arc routing problem , 2006, Comput. Oper. Res..

[8]  D. P. Roland.  Space mission operations DBMS (SMOD) , 2006 .

[9]  Li-Pei Wong,et al.  A Bee Colony Optimization Algorithm for Traveling Salesman Problem , 2008, 2008 Second Asia International Conference on Modelling & Simulation (AMS).

[10]  Alexander Stepanov,et al.  Production , Manufacturing and Logistics Multi-objective evacuation routing in transportation networks , 2009 .

[11]  Michel Gendreau,et al.  An exact epsilon-constraint method for bi-objective combinatorial optimization problems: Application to the Traveling Salesman Problem with Profits , 2009, Eur. J. Oper. Res..

[12]  Keivan Ghoseiri,et al.  An ant colony optimization algorithm for the bi-objective shortest path problem , 2010, Appl. Soft Comput..

[13]  Hehua Ju,et al.  An improvement of D∗ lite algorithm for planetary rover mission planning , 2011, 2011 IEEE International Conference on Mechatronics and Automation.

[14]  David Pisinger,et al.  Multi-objective and multi-constrained non-additive shortest path problems , 2011, Comput. Oper. Res..