Dynamic Temporal Planning for Multirobot Systems

The use of automated action planning techniques is essential for efficient mission execution of mobile robots. However, a tremendous effort is needed to represent planning problem domains realistically to meet the real-world constraints. Therefore, there is another source of uncertainty for mobile robot systems due to the impossibility of perfectly representing action representations (e.g., preconditions and effects) in all circumstances. When domain representations are not complete, a planner may not be capable of constructing a valid plan for dynamic events even when it is possible. This research focuses on a generic domain update method to construct alternative plans against real-time execution failures which are detected either during runtime or earlier by a plan simulation process. Based on the updated domain representations, a new executable plan is constructed even when the outcomes of existing operators are not completely known in advance or valid plans are not possible with the existing representation of the domain. A failure resolution scenario is given in the realistic Webots simulator with mobile robots. Since TLPlan is used as the base temporal planner, makespan optimization is achieved with the available knowledge of the robots.