Biologically inspired visual odometer for navigation of a flying robot

Experimental research in biology has uncovered a number of different ways in which flying insects use cues derived from optical flow for navigational purposes, such as safe landing, obstacle avoidance and dead reckoning. In this study, we use a synthetic methodology to gain additional insights into the navigation behavior of bees. Specifically, we focus on the mechanisms of course stabilization behavior and visually mediated odometer by using a biological model of motion detector for the purpose of long-range goal-directed navigation in 3D environment. The performance tests of the proposed navigation method are conducted by using a blimp-type flying robot platform in uncontrolled indoor environments. The result shows that the proposed mechanism can be used for goal-directed navigation. Further analysis is also conducted in order to enhance the navigation performance of autonomous aerial vehicles. © 2003 Elsevier B.V. All rights reserved.

[1]  Christof Koch,et al.  A Neuromorphic Visual Motion Sensor For Real-World Robots , 1998 .

[2]  M. Srinivasan,et al.  Reflective surfaces for panoramic imaging. , 1997, Applied optics.

[3]  Svetha Venkatesh,et al.  How honeybees make grazing landings on flat surfaces , 2000, Biological Cybernetics.

[4]  M V Srinivasan,et al.  Honeybee navigation: nature and calibration of the "odometer". , 2000, Science.

[5]  Zhang,et al.  Visually mediated odometry in honeybees , 1997, The Journal of experimental biology.

[6]  Thomas Netter,et al.  A robotic aircraft that follows terrain using a neuromorphic eye , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Heinrich H. Bülthoff,et al.  Insect Inspired Visual Control of Translatory Flight , 2001, ECAL.

[8]  Fabrizio Mura,et al.  Visual control of altitude and speed in a flying agent , 1994 .

[9]  Takeo Kanade,et al.  A visual odometer for autonomous helicopter flight , 1999, Robotics Auton. Syst..

[10]  Mandyam V. Srinivasan,et al.  Motion detection in insect orientation and navigation , 1999, Vision Research.

[11]  Giulio Sandini,et al.  Divergent stereo for robot navigation: learning from bees , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[12]  N. Franceschini,et al.  From insect vision to robot vision , 1992 .

[13]  F. A. Miles,et al.  Visual Motion and Its Role in the Stabilization of Gaze , 1992 .

[14]  George A. Bekey,et al.  The USC autonomous flying vehicle: an experiment in real-time behavior-based control , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[15]  Svetha Venkatesh,et al.  Robot navigation inspired by principles of insect vision , 1999, Robotics Auton. Syst..

[16]  Heinrich H. Bülthoff,et al.  On robots and flies: Modeling the visual orientation behavior of flies , 1999, Robotics Auton. Syst..

[17]  Simon Fürst,et al.  A vision based navigation system for autonomous aircraft , 1999, Robotics Auton. Syst..

[18]  Nicolas H. Franceschini,et al.  Towards UAV Nap-of-the-Earth Flight Using Optical Flow , 1999, ECAL.

[19]  W. Reichardt.  Movement perception in insects , 1969 .

[20]  Alexandre Bernardino,et al.  Visual station keeping for floating robots in unstructured environments , 2002, Robotics Auton. Syst..

[21]  Zhang,et al.  Honeybee navigation en route to the goal: visual flight control and odometry , 1996, The Journal of experimental biology.

[22]  W. Tuckwell,et al.  The Honey Bee , 1891, Nature.