Towards an Understanding of the Impact of Autonomous Path Planning on Victim Search in USAR Paul...
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Transcript of Towards an Understanding of the Impact of Autonomous Path Planning on Victim Search in USAR Paul...
Towards an Understanding of the Impact of Autonomous Path
Planning on Victim Search in USAR
Paul Scerri, Prasanna Velagapudi, Katia Sycara, Huadong Wang, Shih-Yi James Chien and Michael
Lewis
Robotics Institute, Carnegie Mellon UniversitySchool of Information Sciences, University of
Pittsburgh
Urban Search and Rescue
• Focus on Chemical, Biological, Radiological, Nuclear events
• Use multiple robots to search for victims in dangerous urban disaster environment
• Complex environment means that humans are required
Operator Tasks
• Operator has several independent tasks
• Processing vision data (identifying victims/problems)
• Rescuing stuck or broken robots (trapped under chairs or high centered)
• Planning exploration
• Coordinating robots
Increasing Robot:Operator Ratio
• Operators are extremely expensive compared to robots
• Easier to get more robots than more operators
• Robots spend much of their time moving slowly between locations
• Operator time is not efficiently utilized
• Unpredictably required
Autonomous Path Planning
• Robots are already performing SLAM w/ LIDAR data
• Allow robots to plan their own paths, to cooperatively explore the environment
• Path planning is mature, reasonably reliable in some environments
• Suspect that operators spend a lot of effort thinking about path planning, for little gain
Tradeoffs of Autonomy
• Large amount of operator time saved, corresponding increase in efficiency
• Robots use abstracted data to decide where to explore, human insight/semantic knowledge might be more efficient
• Operators may lose some situational awareness if they don’t need to control robots
Lattice Planning
• Straightforward implementation of published algorithms
• Nodes valued by expected information gain of going to that location
• Edges valued by probability of traversing safely
• Thresholded, with bias against paths of other robots
• Branch and bound search to find path that maximizes information gain
• Some limits on path length, preference for straightness, etc.
USARSim
• High-fidelity simulator based on Unreal Tournament
• Real-time physics with physics card
• Open source, freely available
• Maintained by NIST
Experiment Design
• 60 paid subjects in 30 teams of 2 used both designs
• 24 P3ATs, 25 min., large office environment, find/mark victims
• Auto:
• Path planner, with operator able to teleop or waypoint plan
• Manual:
• Waypoint planning for each robot, teleop when required
Conclusions
• Autonomous path planning a useful way of reducing operator load when environment allows it
• Benefits (faster planning, handling more robots) outweigh costs (loss of situation awareness, lack of human insight)
• Operator’s time taken up with other activities
• Not clear they fully exploit all robots
• Future focus on data presentation/visualization