Bio-inspired trajectory generation for UAV perching

This paper represents a bio-inspired trajectory generation (path planning) method for UAV perching. The method is based on the tau theory which was established from studying the natural motion behaviors when animals (including humans) approaching and catching a fixed or moving object. In our research, the tau theory is applied to the trajectory generation problem of a UAV perching on a target object. Two perching scenarios have been studied, one from a flight state (with non-zero initial velocity) and one from a hovering state (with zero initial velocity). Three strategies, namely, perching with a straight-line trajectory, perching with pitch angle coupling, and perching with pitch/yaw angular coupling, are demonstrated with each of the two scenarios. The simulation results show that the resulting flight trajectories meet all the desired requirements for a rotary UAV to perch on an object.

[1]  Russ Tedrake,et al.  Control synthesis and verification for a perching UAV using LQR-Trees , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[2]  Russ Tedrake,et al.  Experiments in Fixed-Wing UAV Perching , 2008 .

[3]  Anthony M. Norcia,et al.  Development of sensitivity to information for impending collision , 1977 .

[4]  Michael F. Land,et al.  Lee's 1976 Paper , 2009 .

[5]  David N. Lee.  Guiding Movement by Coupling Taus , 1998 .

[6]  Mark A. Minor,et al.  Avian-inspired passive perching mechanism for robotic rotorcraft , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  David N. Lee,et al.  VISUAL CONTROL OF VELOCITY OF APPROACH BY PIGEONS WHEN LANDING , 1993 .

[8]  Vijay Kumar,et al.  Design, modeling, estimation and control for aerial grasping and manipulation , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Ephrahim Garcia,et al.  Optimization of Perching Maneuvers Through Vehicle Morphing , 2008 .

[10]  Christoph Hürzeler,et al.  A perching mechanism for micro aerial vehicles , 2009 .

[11]  David N. Lee,et al.  Plummeting gannets: a paradigm of ecological optics , 1981, Nature.

[12]  Joseph L. Moore,et al.  Powerline perching with a fixed-wing UAV , 2009 .

[13]  Farid Kendoul,et al.  Bio-inspired TauPilot for automated aerial 4D docking and landing of Unmanned Aircraft Systems , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[14]  David N. Lee.  General Tau Theory: evolution to date. , 2009, Perception.

[15]  James A. Caviness,et al.  Persistent Fear Responses in Rhesus Monkeys to the Optical Stimulus of "Looming" , 1962, Science.

[16]  Daniel Mellinger,et al.  Control of Quadrotors for Robust Perching and Landing , 2010 .

[17]  Paul B Rock,et al.  Tau as a potential control variable for visually guided braking. , 2006, Journal of experimental psychology. Human perception and performance.

[18]  David N. Lee,et al.  A Theory of Visual Control of Braking Based on Information about Time-to-Collision , 1976, Perception.

[19]  Michael Jump,et al.  Investigation of the Flare Maneuver Using Optical Tau , 2006 .

[20]  H. Wagner.  Flow-field variables trigger landing in flies , 1982, Nature.

[21]  D. Regan,et al.  Hitting what one wants to hit and missing what one wants to miss , 2001, Vision Research.

[22]  Mark R. Cutkosky,et al.  Region of attraction estimation for a perching aircraft: A Lyapunov method exploiting barrier certificates , 2012, 2012 IEEE International Conference on Robotics and Automation.

[23]  Fred Sir Hoyle,et al.  The Black Cloud , 1957 .

[24]  G. Laurent,et al.  Elementary Computation of Object Approach by a Wide-Field Visual Neuron , 1995, Science.

[25]  B. Frost,et al.  Computation of different optical variables of looming objects in pigeon nucleus rotundus neurons , 1998, Nature Neuroscience.

[26]  Marion A. Eppler,et al.  Development of Visually Guided Locomotion , 1998 .

[27]  Peter A. Hancock,et al.  Time-to-contact , 1998 .