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Wearable Computing meets MAS: A real-world interface for the RoboCupRescue simulation platform

Wearable Computing meets MAS: A real-world interface for the RoboCupRescue simulation platform. Motivation Wearable computing Data integration MAS solutions for USAR. * University of Freiburg ** Center of Computing Technology (TZI) Bremen.

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Wearable Computing meets MAS: A real-world interface for the RoboCupRescue simulation platform

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  1. Wearable Computing meets MAS: A real-world interface for the RoboCupRescue simulation platform Motivation Wearable computing Data integration MAS solutions for USAR * University of Freiburg ** Center of Computing Technology (TZI) Bremen

  2. Why to integrate sensor data during search and rescue? • Situation awareness: • Where am I: problem of self-localization • Where to go: Connectivity between places has changed • What to communicate: Destroyed places are difficult to describe • Getting simulation and MAS closer to reality: • Exchange of real data for analysis and training • Development and improvement of disaster simulators • Close-to-reality development of multi-agent software A. Kleiner, N. Behrens and H. Kenn

  3. The current test system • GPS-based localization and data collection with a wearable device • No additional cognitive load, e.g. system collects data in the background • Trajectories are collected and send to a server via GPRS/UMTS • Data integration on the server-side • Generation of connectivity network annotated with observations • Data exchange with the RoboCup Rescue kernel via the GPX protocol • Coordination of exploration and victim search GPS PC 3GPhone A. Kleiner, N. Behrens and H. Kenn

  4. Data Integration ExampleIntegration from data collected by the wearable computer To Google earth (GPX) To RoboCup Rescue A. Kleiner, N. Behrens and H. Kenn

  5. Open research problemImproving GPS accuracy in urban areas • GPS routing on a road network is solved?! • Urban Search And Rescue: • Road network destroyed • Multiple signal path problem if close to buildings • Weak signal within buildings • Solution: Multi-agent SLAM* by agents attached to humans GPS Track on a cloudy day *Simultaneous Localization And Mapping (SLAM) A. Kleiner, N. Behrens and H. Kenn

  6. Based on the work of Q. Ladetto at EPFL Idea: Estimate length and direction of step based on motion sensor data Fusion of GPS and PDR position estimates Implementation: Michael Dippold (Master Student at TZI) http://auriga.wearlab.de/projects/leica/ Red: GPS Data (Tuesday, clear sky) Green: GPS + PDR fusion Pedestrian Dead Reckoning GPS Jump GPS lost A. Kleiner, N. Behrens and H. Kenn

  7. Solution for the future:Application of a SLAM technique, borrowed from robotics • MA SLAM implies a data association and estimation problem • Pose estimation: • Dead reckoning from accelerometers, gyroscopes and step counters • Data association: • Partially GPS localization with high accuracy, e.g. if close to stationary posts outside the buildings • Detection of RFID tags within buildings • Central integration of data from multiple agents RFIDWristband A. Kleiner, N. Behrens and H. Kenn

  8. MAS support for USARExample1: Dijkstra based travel time estimation • Legend • Red (bright to dark)  estimated travel time • White  unreachable area A. Kleiner, N. Behrens and H. Kenn

  9. MAS support for USARExample2: Informed coordination of victim search • Legend • Yellow  Targets assigned by the station • Green  Found victims • White  Explored buildings A. Kleiner, N. Behrens and H. Kenn

  10. Future visions • Distributed SLAM by “wearable” agents, attached to human task forces • RoboCup Rescue as a unified MAS benchmark based on real data • RoboCup Rescue as an unified platform for responders to train and evaluate real rescue missions A. Kleiner, N. Behrens and H. Kenn

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