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Dynamic Mission Planning for Multiple Mobile Robots. Barry Brumitt and Anthony Stentz 26 Oct, 1999 AMRS-99 Class Presentation Brian Chemel. Overview. Problem description Mission grammar System architecture: GRAMMPS Brief digression: D* Results Analysis and limitations.
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Dynamic Mission Planning for Multiple Mobile Robots Barry Brumitt and Anthony Stentz 26 Oct, 1999 AMRS-99 Class Presentation Brian Chemel
Overview • Problem description • Mission grammar • System architecture: GRAMMPS • Brief digression: D* • Results • Analysis and limitations Dynamic Mission Planning for Multiple Mobile Robots
Problem Description: Environment • Dynamic, complex environment • Typical situation • World state initially unknown • Runtime observations incorporated into shared world model Dynamic Mission Planning for Multiple Mobile Robots
Problem Description: Robots • Multiple, heterogeneous mobile robots • Assumptions • Robots have relatively open workspaces, so solution set is not too sparse • Effective positioning, communication and perception are a given Dynamic Mission Planning for Multiple Mobile Robots
Problem Description: Goals • Robot task: move to specified locations, in specified order • Reconnaissance example • Waypoints to be scouted by team of robots • Warehouse example • Multiple pickup points, to be followed by multiple delivery points Dynamic Mission Planning for Multiple Mobile Robots
Problem Description: GRAMMPS Planner • Military reconnaissance task • Outdoor environment • Multiple robot vehicles (Navlab HMMWV’s, in practice) • Multiple distributed goals, with sequencing • Requires mission grammar to pass parameters to distributed planning system Dynamic Mission Planning for Multiple Mobile Robots
Mission Grammar Dynamic Mission Planning for Multiple Mobile Robots
Mission Grammar: Example • “Move either robot 1 or robot 2 to goals 1, 2, 3, and 4. Then move both robots 1 and 2 to goal 5.” Dynamic Mission Planning for Multiple Mobile Robots
System Architecture: Overview Dynamic Planners (one per goal) • Global (shared) dynamic planners • Global (shared) mission planner • Local (individual) plan execution … D* D* D* D* D* Mission Planner Robot 1 Robot 2 Robot n … Dynamic Mission Planning for Multiple Mobile Robots
System Architecture: Local Navigators Dynamic Planners (one per goal) • Input • Path to assigned goal • Perception information • Output • Steering commands … D* D* D* D* D* Mission Planner Robot 1 Robot 2 Robot n … Dynamic Mission Planning for Multiple Mobile Robots
System Architecture: Mission Planner Dynamic Planners (one per goal) • Input • Estimated path costs for each (robot,goal) pair • Output • Mapping from robots to goals • Algorithm • TSP heuristic … D* D* D* D* D* Mission Planner Robot 1 Robot 2 Robot n … Dynamic Mission Planning for Multiple Mobile Robots
System Architecture:Dynamic Planners Dynamic Planners (one per goal) • Input • Current world state knowledge • Output • Path to each goal for each robot • Planning algorithm • D* … D* D* D* D* D* Mission Planner Robot 1 Robot 2 Robot n … Dynamic Mission Planning for Multiple Mobile Robots
Brief Digression: The D* Algorithm • Modification of the A* planning algorithm • Provides efficient, optimal and complete path planning in unknown, partially known, and changing environments • As new information about the environment is learned, cost information is propagated through state space • Each time new information makes previous path calculations obsolete, a new path is calculated • Original paper: Stentz, ICRA ‘94 Dynamic Mission Planning for Multiple Mobile Robots
Example: Simulation Initial Plan • Mission statement: Dynamic Mission Planning for Multiple Mobile Robots
Example: Simulation Final Plan • Goals re-assigned on the fly • Mission successfully completed Dynamic Mission Planning for Multiple Mobile Robots
Highlights • Demonstration implementation on Navlab HMMWVs allows real-time, team-based mission planning in dynamic environments • System scales gracefully up to large numbers of robots and goals Dynamic Mission Planning for Multiple Mobile Robots
Limitations • Waypoint task structure is very limiting • No discussion of how to modify TSP approach to allow heterogeneity • One robot must act as “leader” of the entire team • When D* fails, system can lock up Dynamic Mission Planning for Multiple Mobile Robots
Related Work • Stentz, T. “Optimal and Efficient Path Planning for Partially-Known Environments.” ICRA ’94 • Brumitt, B., Stentz, T. “GRAMMPS: A Generalized Mission Planner for Multiple Mobile Robots in Unstructured Environments.” ICRA ‘98 • Brumitt, B., Hebert, M. “Experiments in Autonomous Driving With Concurrent Goals and Multiple Vehicles.” ICRA ‘98 Dynamic Mission Planning for Multiple Mobile Robots