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  • 2013

  • Kuderer, Markus; Kretzschmar, Henrik; Sprunk, Christoph; Burgard, Wolfram (2013) : Feature-Based Prediction of Trajectories for Socially Compliant Navigation In: Roy, Nicholas; Newman, Paul; Srinivasa, Siddhartha (Hg.): Robotics: Science and systems VIII: Cambridge, Massachusetts: The MIT Press

    DOI: https://doi.org/10.7551/mitpress/9816.003.0030 

    Abstract: Mobile robots that operate in a shared environmentwith humans need the ability to predict the movements ofpeople to better plan their navigation actions. In this paper, wepresent a novel approach to predict the movements of pedestrians.Our method reasons about entire trajectories that arise frominteractions between people in navigation tasks. It applies amaximum entropy learning method based on features that capturerelevant aspects of the trajectories to determine the probabilitydistribution that underlies human navigation behavior. Hence, ourapproach can be used by mobile robots to predict forthcominginteractions with pedestrians and thus react in a socially compliantway. In extensive experiments, we evaluate the capability andaccuracy of our approach and demonstrate that our algorithmoutperforms the popular social forces method, a state-of-the-artapproach. Furthermore, we show how our algorithm can be usedfor autonomous robot navigation using a real robot.

    Keywords: Mobile Roboter, mobile service robots, Mobiler Roboter, pedestrian, Proxemik, Robotics, socially aware robot navigation, Socially compliant navigation, Soziosensitive Systeme, street, trajectorie, Trajektorie, Verkehr, Verkehrsroboter
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