Bioinspired 4D Trajectory Generation for a UAS Rapid Point-to-Point Movement

doi:10.1016/S1672-6529(14)60021-4

Abstract

Abstract:

A bioinspired trajectory generation approach for Unmanned Aerial System (UAS) rapid Point-to-Point (PTP) movement was presented. The approach was based on general tau theory developed by biologists from observing and studying the behavior of birds and some other animals. We applied the bioinspired approach to the rapid PTP movement problem of a rotary UAS and derived two different trajectory planning strategies, namely, the tau coupling strategy and the intrinsic tau gravity guidance strategy. Based on general tau theory, according to the dynamic model of UAS, we presented a new strategy named intrinsic tau jerk guidance which can fit the movement that the initial acceleration of the UAS is zero. With new strategies, flight trajectory generation examples with a UAS were presented. The kinematics and dynamics analyses of the UAS for rapid PTP movement were presented with simulation results which show that the generated trajectories were feasible.

Key words: bioinspired, trajectory generation, tau theory, jerk guidance, rapid point-to-point movement

Zhen Zhang, Shutao Zhang, Pu Xie, Ou Ma. Bioinspired 4D Trajectory Generation for a UAS Rapid Point-to-Point Movement[J].J4, 2014, 11(1): 72-81.

References

[1] Goerzen C, Kong Z, Mettler B. A survey of motion planning algorithms from the perspective of autonomous UAS guid-ance. Journal of Intelligent and Robotic Systems, 2010, 57, 65–100.

[2] Farid K. Survey of advances in guidance, navigation and control of unmanned rotocraft system. Journal of Field Robotics, 2012, 29, 315–378.

[3] Castillo C L, Moreno W, Valavanis K P. Unmanned heli-copter waypoint trajectory tracking using model predictive control. Proceedings of the 15th Mediterranean Conference on Control and Automation, Athens, Greece, 2007, T27-018.

[4] Mellinger D, Michael N, Kumar V. Trajectory generation and control for precise aggressive maneuvers with quadro-tors. International Journal of Robotics Research, 2012, 31, 664–674.

[5] Moore J, Tedrake R. Powerline perching with a fixed-wing UAS. Proceedings of the AIAA Conference, Seattle, USA, 2009.

[6] Mellinger D, Lindsey Q, Shomin M, Kumar V. Design, modeling, estimation and control for aerial grasping and manipulation. IEEE/RSJ International Conference Intelli-gent Robots and Systems, San Francisco, USA, 2011, 2668–2673.

[7] Doyle C E, Bird J J, Isom T A, Johnson C J, Kallman J C, Simpson J A, King R J, Abbott J J, Minor M A. Avian-inspired passive perching mechanism for robotic ro-torcraft. IEEE/RSJ International Conference Intelligent Robots and Systems, San Francisco, USA, 2011, 4975–4980.

[8] Cory R, Tedrake R. Experiment in fixed-wing UAS perching. Proceedings of the AIAA Guidance, Navigation, and Control Conferenc, AIAA, Honolulu, USA, 2008.

[9] Wickenheiser A M, Garcia E. Optimization of perching maneuvers through vehicle morphing. Journal of Guidance, Control, and Dynamics, 2008, 31, 815–823.

[10] Hecht H, Savelsbergh G J P. Time-to-Contact. Elsevier, Amsterdam, Holand, 2004.

[11] Hoyle F. The Black Cloud. Penguin Books, Harmondsworth, UK, 1957, 26–27.

[12] Regan D, Gray R. Hitting what one wants to hit and missing what one wants to miss. Vision Research, 2001, 41, 3321–3329.

[13] Schiff W, Caviness J A, Gibson J J. Persistent fear responses in rhesus monkeys to the optical stimulus of “Looming”. Science, 1962, 136, 982–983.

[14] Yonas A, Bechtold A G, Frankel D, Gordon F R, McRoberts G, Norcia A, Sternfels S. Development of sensitivity to in-formation for impending collision. Attention, Perception, & Psychophysic, 1977, 21, 97–104.

[15] Lee D N. Theory of visual control of traking based on in-formation about time-to-collision. Perception, 1976, 5, 437–459.

[16] Lee D N, Reddish P E. Plummeting gannets: a paradigm of ecological optics. Nature, 1981, 293, 293–294.

[17] Lee D N, Davies M, Green P R, Van Del Well F R. Visual control of velocity of approach by pigeons when landing. Journal of Experimental Biology, 1993, 180, 85–104.

[18] Lee D N. Guiding movement by coupling Taus. Ecological Psychology, 1998, 10, 221–250.

[19] Lee D N. General Tau Theory: evolution to date. Perception, 2009, 38, 837–850.

[20] Wagner H. Flow-field variables trigger landing in flies. Nature, 1982, 297, 147–148.

[21] Hatsopoulos N, Gabbiani F, Laurent G. Elementary compu-tation of object approach by a wide-field visual neuron. Science, 1995, 270, 1000–1003.

[22] Sun H, Frost B J. Computation of different optical variables of looming objects in pigeon nucleus rotundus neurons. Nature Neuroscience, 1998, 1, 296–303.

[23] Rock P, Harris M G. Tau-dot as a potential control variable for visually guided braking. Journal of Experimental Psychology: Human Perception and Performance, 2006, 32, 251–267.

[24] Jump M, Padfield G D. Investigation of the flare maneuver using optical tau. Journal of guidance, control, and dynam-ics, 2006, 29, 1189–1200.

[25] Kendoul F, Ahmed B. Bio-inspired TauPilot for automated aerial 4D docking and landing of unmanned aircraft systems. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, Portugal, 2012, 480–487.

[26] Zhang Z, Xie P, Ma O. Bio-inspired trajectory generation for UAS perching. IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Wollongong, Australia, 2013, 997–1002.

[27] Abend W, Bizzi E, Morasso P. Human arm trajectory for-mation. Brain, 1982, 105, 331–348.

[28] Nagasaki H. Asymmetric velocity and acceleration profiles of human arm movements. Experimental Brain Research, 1989, 74, 319–326.

[29] Todorov E. Optimality principles in sensorimotor control. Nature Neuroscience, 2004, 7, 907–915.

[30] Fligge N, McIntyre J, van der Smagt P. Minimum jerk for human catching movements in 3D. The Proceedings of the 4th IEEE RAS/EMBS International Conference on Bio-medical Robotics and Biomechatronics, Roma, Italy, 2012, 581–586.

[31] Xie P, Ma O. Development of a bio-inspired UAS perching system. ASME-IDETC/CIE, Portland, USA, 2013.

[32] Xie P, Ma O, Zhang Z. A bio-inspired approach for UAS landing and perching. 2013 AIAA/GNC, Boston, USA, 2013.

[33] Flores-Abad A, Xie P, Arredondo G M, Ma O. Test of a special inertial measurement unit using a quadrotor aircraft. AIAA/GNC, Minneapolis, USA, 2012.

[34] Corke P I. Robotics, Vision & Control: Fundamental Algorithms in MATLAB. Springer-Verlag Berlin/Heidelberg, Germany, 2011.

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