An Efficient Algorithm for Environmental Coverage with Multiple Robots
Tasks such as street mapping and security surveillance seek a route that traverses a given space to perform a function. These task functions may involve mapping the space for accurate modeling, sensing the space for unusual activity, or searching the space for an object. In many cases, the use of multiple robots can greatly improve the performance of these tasks. We assume a prior map is available, but it may be inaccurate due to factors such as occlusion, age, dynamic objects, and resolution limitations. In this work, we address the NP-hard problem of environmental coverage with incomplete prior map information using k robots. To utilize related algorithms in graph theory, we represent the environment as a graph and model the coverage problem as a k-Rural Postman Problem. Using this representation, we present a graph coverage approach for plan generation that can handle graph changes online. Our approach proposes two improvements to an existing heuristic algorithm for the coverage problem. Our improvements seek to equalize the length of the k paths by minimizing the length of the maximum tour. We evaluate our approach on a set of comparison tests in simulation.
Ling Xu Anthony (Tony) Stentz
Robotics Institute,Carnegie Mellon University,Pittsburgh,PA,USA
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
4950-4955
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）