A Framework with a Pedestrian Simulator for Deploying Robots into a Real Environment

We describe a simulation framework aimed to develop and test robots before deploying them in a real environment crowded with pedestrians. In order to use mobile robots in the real world, it is necessary to test whether they are able to navigate well, i.e. without causing safety risks to humans. This task is particular difficult due to the complex behavior pedestrians have towards each other and also towards the robot, that can be perceived either as an obstacle to avoid or as an object of interest to approach for curiosity. To overcome this difficulty, our framework involves a pedestrian simulator, based on a collision avoidance model developed to describe low density conditions as those occurring in shopping malls, to test the robot's navigation capability among pedestrians. Furthermore, we analyzed the behavior of pedestrians towards a robot in a shopping mall to build a human-to-robot interaction model that was introduced in the simulator. Our simulator works as a tool to test the level of safety of robot navigation before deploying it in a real environment. We demonstrate our approach showing how we used the simulator, and how the robot finally navigated in a real environment.

[1]  Takayuki Kanda,et al.  Abstracting People's Trajectories for Social Robots to Proactively Approach Customers , 2009, IEEE Transactions on Robotics.

[2]  T. Kanda,et al.  Social force model with explicit collision prediction , 2011 .

[3]  Horst-Michael Groß,et al.  TOOMAS: Interactive Shopping Guide robots in everyday use - final implementation and experiences from long-term field trials , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  Stefano Carpin,et al.  USARSim: a robot simulator for research and education , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[5]  Rachid Alami,et al.  Planning Safe and Legible Hand-over Motions for Human-Robot Interaction , 2010 .

[6]  Stefan Ulbrich,et al.  OpenGRASP: A Toolkit for Robot Grasping Simulation , 2010, SIMPAR.

[7]  Yuan Xu,et al.  An Approach to Close the Gap between Simulation and Real Robots , 2010, SIMPAR.

[8]  Norman I. Badler,et al.  Controlling individual agents in high-density crowd simulation , 2007, SCA '07.

[9]  Hiroshi Ishiguro,et al.  Laser-Based Tracking of Human Position and Orientation Using Parametric Shape Modeling , 2009, Adv. Robotics.

[10]  Dirk Helbing,et al.  Simulating dynamical features of escape panic , 2000, Nature.

[11]  Wolfram Burgard,et al.  The Interactive Museum Tour-Guide Robot , 1998, AAAI/IAAI.

[12]  P. Cochat,et al.  Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.

[13]  Ivan Petrovic,et al.  Dynamic window based approach to mobile robot motion control in the presence of moving obstacles , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[14]  M. Asada,et al.  SimSpark – Concepts and Application in the RoboCup 3 D Soccer Simulation League , 2008 .

[15]  Bilge Mutlu,et al.  Robots in organizations: The role of workflow, social, and environmental factors in human-robot interaction , 2008, 2008 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[16]  Rachid Alami,et al.  A Human Aware Mobile Robot Motion Planner , 2007, IEEE Transactions on Robotics.

[17]  Han-Pang Huang,et al.  Motion planning of a dual-arm mobile robot in the configuration-time space , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Francesc Moreno-Noguer,et al.  Discrete time motion model for guiding people in urban areas using multiple robots , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[19]  Christian Vollmer,et al.  Learning to navigate through crowded environments , 2010, 2010 IEEE International Conference on Robotics and Automation.