Abstract—This paper provides an alternative approach to the co-operative multi-robot path planning problem using parallel differential evolution algorithms. Both centralized and distributed realizations for multi-robot path planning have been studied, and the performances of the methods have been compared with respect to a few pre-defined yardsticks. The distributed approach to this problem out-performs its centralized ver sion for multi-robot planning. Relative performance of the distributed version of the differential evolution algorithm has been studied with varying numbers of robots and obstacles. The distributed version of the algorithm is also compared with a PSO-based realization, and the results are competitive. I. INTRODUCTION HE late 1990s have seen a significant progress in mobile robotics [1], [2], [3]. Path planning is regarded as a fundamental problem in mobile robotics. Given a world map for a robot, the path planning problem [31] attempts to determine a trajectory of motion for the robot from a predefined starting point to a given goal point without colliding with any obstacle in the map. The basic path planning problem has several extensions and classifications. One common classification of the problem includes local and global planning [12], [13], [14], [15]. In local path planning a robot navigates through the obstacle map in steps and determines its next position toward the goal, satisfying one or more predefined constraints on path-, time- or energy- optimality [4], [5], [6], [7], [10], [11]. In global planning, on the other hand, the robot plans the entire path prior to its movement towards the goal. Such type of global planning is sometimes referred to as offline planning in the literature [32]. Significant progress on single robot motion planning [34], [35], [5] has been attained in mobile robotics over the last three decades. Classical approaches such as quad-tree [34], graph-based, voronoi-diagram, heuristic algorithms such as Jayasree Chakraborty is with Department of Electronics and Tele- Communication Engineering, Jadavpur University, Kolkata 700032, India (phone: +91 33 25142396; e-mail: jayasree2@gmail.com). Amit Konar, is with Department of Electronics and Tele- Communication Engineering, Jadavpur University, Kolkata 700032, India (e-mail: konaramit@yahoo.co.in). Uday K. Chakraborty is with Department of Computer Science, University of Missouri, St. Louis, MO 63121 (phone: +1 314 5166339; e- mail: chakrabortyu@umsl.edu ). L. C. Jain is with Knowledge-Based Intelligent Engineering Systems Centre, University of South Australia, Adelaide, SA 5095, Australia (e- mail: lakhmi.jain@unisa.edu.au). real time A* [23], neural [35] and evolutionary [5] algorithms are some of the well-known techniques for path planning. In a multi-robot motion planning problem, each robot has a predefined starting and goal position in a given world map and the robots have to plan their paths, either globally or locally, without hitting any of the teammates or obstacles. The obstacles may be stationary or dynamic. However, we in this paper consider stationary obstacles in the given world map for the robots. The path-planning problem in the given context attempts to minimize the total distance traveled by the robots in the given workspace, subject to the constraint that the robots do not hit each other or the static obstacles. It may be noted that like the single robot path planning problem, the multi-robot path planning is an NP- complete [16] problem, as no polynomial time algorithm to solve the problem is known at this time [9]. Researchers are keen to consider geometry/topology- based path planning problems for multi-robot systems. In a geometry-based path planning problem [17], [15], the obstacle location and the geometry of the environment are considered, whereas in a topology-sensitive path planning system [18], [19], a specialized data structure, such as a graph, describing the paths among different regions of the robots’ world map is considered. In a recent work [20], researchers employed a hierarchical decomposition of sub- graph, describing road maps for the robots, for topology- sensitive path planning for multiple robots. Such works are more effective for obstacle-free environment. The multi-robot path-planning problem can broadly be realized by two distinct approaches, centralized and distributed. In the centralized approach [18], [21], [22], the objective functions and the constraints for path/motion planning of all the robots are considered together. The computation for local planners by the centralized approach is too costly, and thus is not amenable to real-time realization. On the contrary, the distributed approach divides the complexity of centralized path planning into problems of small complexity to be shared by the robots. Consequently, in distributed planning, each robot attempts to construct its path almost independently, avoiding collision with static obstacles or teammates engaged in path planning. Most of the distributed planning algorithms attempt to handle the problem into distinct phases. In the 1 st phase, the paths for the individual robots are constructed, ignoring the presence of other robots. In the 2 nd phase, the paths of the robots are retuned in order to avoid collision with other robots. One fundamental problem of this approach lies in Distributed Cooperative Multi–Robot Path Planning Using Differential Evolution Jayasree Chakraborty, Amit Konar, Uday K. Chakraborty and L.C. Jain T 718 978-1-4244-1823-7/08/$25.00 c 2008 IEEE