Planning Motion Among Moving Objects
supported by NSF
Samuel Rodriguez, Jyh-Ming Lien, Nancy M. Amato

In this paper we present a heuristic approach to planning in an uncertain environment with moving obstacles. Our approach assumes that the robot has no knowledge of the future trajectory of the moving objects. Our framework also distinguishes between two types of moving objects:hard and soft objects in the environment. We distinguish between the two types of objects in the environment as varying application domains could allow for some collision between moving objects.

A test environment showing different aspects considered in our planning framework. These aspects include (a) a robot, (b) soft objects (other agents), (c) hard objects, (d) a global-dynamic roadmap and (e) kinodynamic local plans.

We propose a two stage approach to planning in uncertain environments. The first stage maintains information about the global connectivity of the environment. In this stage of planning, only hard objects are considered. Global connectivity is approximated using a global dynamic roadmap which is updated as the environment changes. As a result, approximate global paths can be extracted from the global dynamic roadmap that is free of hard objects. The second stage uses a global path extracted from the dynamic roadmap to locally plan in the environment. These kinodyanmic local plans take into account the soft objects, or neighboring other agents, to find safe plans. The local paths are also updated as the environment changes. For more information please refer to the paper.

Simulation Results:

	Number Of Agents:    0 1 5 10 20   movie movie movie movie movie
	Number Of Agents:    0 5 10 20   movie movie movie movie
	Number Of Agents:    2 4 6 8 10 15   movie movie movie movie movie movie

Related Projects

Group Behaviors using Rule-Based Roadmaps
Shepherding Behaviors
Composable Group Behaviors

Papers

A Framework for Planning Motion in Environments with Moving Obstacles, Sam Rodriguez, Jyh-Ming Lien, Nancy M. Amato, In Proc. IEEE Int. Conf. Intel. Rob. Syst. (IROS), pp. 3309-3314, Oct 2007. Also, Technical Report, TR06-010, Parasol Laboratory, Department of Computer Science, Texas A&M University, Sep 2007.
Proceedings(ps, pdf, abstract) Technical Report(ps, pdf, abstract)

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