Discrete time motion model for guiding people in urban areas using multiple robots

We present a new model for people guidance in urban settings using several mobile robots, that overcomes the limitations of existing approaches, which are either tailored to tightly bounded environments, or based on unrealistic human behaviors. Although the robots motion is controlled by means of a standard particle filter formulation, the novelty of our approach resides in how the environment and human and robot motions are modeled. In particular we define a ¿Discrete-Time- Motion¿ model, which from one side represents the environment by means of a potential field, that makes it appropriate to deal with open areas, and on the other hand the motion models for people and robots respond to realistic situations, and for instance human behaviors such as ¿leaving the group¿ are considered.

[1]  Helbing,et al.  Social force model for pedestrian dynamics. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[2]  Günther Schmidt,et al.  Path planning and guidance techniques for an autonomous mobile cleaning robot , 1995, Robotics Auton. Syst..

[3]  Kristine L. Bell,et al.  A Tutorial on Particle Filters for Online Nonlinear/NonGaussian Bayesian Tracking , 2007 .

[4]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[5]  Günther Schmidt,et al.  Path planning and guidance techniques for an autonomous mobile cleaning robot , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[6]  Robin R. Murphy,et al.  Human-robot interaction in rescue robotics , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

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

[8]  Robin R. Murphy,et al.  Human-robot interactions during the robot-assisted urban search and rescue response at the World Trade Center , 2003, IEEE Trans. Syst. Man Cybern. Part B.

[9]  Luiz Chaimowicz,et al.  Aerial Shepherds: Coordination among UAVs and Swarms of Robots , 2004, DARS.

[10]  Richard T. Vaughan Experiments in Animal-Interactive Robotics , 1999 .

[11]  Jun Ota,et al.  Cooperative exploration of mobile robots using reaction-diffusion equation on a graph , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[12]  J. Andrade-Cetto,et al.  Ubiquitous networking robotics in urban settings , 2006 .

[13]  D. Helbing,et al.  Self-Organization Phenomena in Pedestrian Crowds , 1998, cond-mat/9806152.

[14]  Petar M. Djuric,et al.  Resampling algorithms and architectures for distributed particle filters , 2005, IEEE Transactions on Signal Processing.

[15]  Cory D. Kidd,et al.  HUMANOID ROBOTS AS COOPERATIVE PARTNERS FOR PEOPLE , 2004 .

[16]  Nancy M. Amato,et al.  Shepherding Behaviors with Multiple Shepherds , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[17]  Shin'ichi Yuta,et al.  Crowding and guiding groups of humans by teams of mobile robots , 2005, IEEE Workshop on Advanced Robotics and its Social Impacts, 2005..

[18]  Stephen Cameron,et al.  Experiments in automatic flock control , 2000, Robotics Auton. Syst..

[19]  Vijay Kumar,et al.  Modeling and control of formations of nonholonomic mobile robots , 2001, IEEE Trans. Robotics Autom..

[20]  Kerstin Dautenhahn,et al.  What is a robot companion - friend, assistant or butler? , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[21]  Narendra Ahuja,et al.  A potential field approach to path planning , 1992, IEEE Trans. Robotics Autom..