Model-based echolocation of environmental objects

This paper presents an algorithm that can recognize and localize objects given a model of their contours using only ultrasonic range data. The algorithm exploits a physical model of the ultrasonic beam and combines several readings to extract outline object segments from the environment. It then detects patterns of outline segments that correspond to predefined models of object contours, performing both object recognition and localization. The algorithm is robust since it can account for noise and inaccurate readings as well as efficient since it uses a relaxation technique that can incorporate new data incrementally without recalculating from scratch.<<ETX>>

[1]  Yoram Koren,et al.  The vector field histogram-fast obstacle avoidance for mobile robots , 1991, IEEE Trans. Robotics Autom..

[2]  Ronald C. Arkin,et al.  Motor Schema — Based Mobile Robot Navigation , 1989, Int. J. Robotics Res..

[3]  Phillip J. McKerrow Echolocation - From range to outline segments , 1993, Robotics Auton. Syst..

[4]  Billur Barshan,et al.  ROBAT: a sonar-based mobile robot for bat-like prey capture , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[5]  Alberto Elfes,et al.  Sonar-based real-world mapping and navigation , 1987, IEEE J. Robotics Autom..

[6]  Billur Barshan,et al.  A bat-like sonar system for obstacle localization , 1992, IEEE Trans. Syst. Man Cybern..

[7]  Yoram Koren,et al.  Real-time obstacle avoidance for fact mobile robots , 1989, IEEE Trans. Syst. Man Cybern..

[8]  Michael Drumheller,et al.  Mobile Robot Localization Using Sonar , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Alberto Elfes,et al.  Using occupancy grids for mobile robot perception and navigation , 1989, Computer.