Guidance laws, obstacle avoidance and artificial potential functions

Advances in Unmanned Marine Vehicles

Volumn , Issue , 2006, Pages 43-66

  Healey, A J ^a  

^a Naval Post Graduate School ^*  (United States)

Author keywords

APF; Artificial potential function; Autopilot function; Collision avoidance; Feedback; Feedback controller; Guidance law; Lateral acceleration; Line of sight; LOS; Marine control; Obstacle avoidance; Proportional guidance; Remotely operated vehicles; Underwater vehicle; Underwater vehicles; Unmanned underwater vehicle; Vehicle speed

Indexed keywords

AIR NAVIGATION; COLLISION AVOIDANCE; FEEDBACK; FEEDBACK CONTROL; NONLINEAR CONTROL SYSTEMS; UNMANNED UNDERWATER VEHICLES; VEHICLES;

ARTIFICIAL POTENTIAL FUNCTIONS; FEEDBACK CONTROLLER; GUIDANCE LAWS; LATERAL ACCELERATION; LINE OF SIGHT; MARINE CONTROL; PROPORTIONAL GUIDANCE; UNDERWATER VEHICLES; VEHICLE SPEED;

REMOTELY OPERATED VEHICLES;

EID: 85014208614     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1049/PBCE069E_ch3     Document Type: Chapter

References (17)

1. Kaminer, I., A. Pascoal, E. Hallberg, and C. Silvestre (1998). Trajectory tracking for autonomous vehicles: an integrated approach to guidance and control. AIAA Journal of Guidance and Dynamics, 21(1), pp. 29-38.
2. Milam, M.B. (2003). Real time trajectory generation for constrained dynamics systems. Ph.D. thesis, Caltech.
3. Kanayama, Y. and B. Hartman (1997). Smooth local path planning for autonomous vehicle. International Journal of Robotics Research, 16(3), pp. 263-284.
4. Fodrea, L. and A.J. Healey (2003). Obstacle avoidance considerations for the REMUS autonomous underwater vehicle. In Proceedings of the ASME OMAE Conference, Paper # OMAE2003-37116.
5. Marco, D.B. and A.J. Healey (2001). Command, control and navigation: experimental results with the NPS ARIES AUV. IEEE Journal of Oceanic Engineering (Special Issue on Autonomous Ocean Sampling Networks), 26(4), pp. 466-477. http://web.nps.navy.mil/~me/healey/papers/ IEEE_Marco_Healey.pdf
6. Healey, A.J. (2001). Dynamics and control of mobile robot vehicles. ME4823 Class Notes, Chapters 1-7. http://web.nps.navy.mil/~me/healey/ME4823/
7. Prestero, T. (2001). Verification of a six-degree of freedom simulation model for theREMUSautonomous underwater vehicle, M.S. thesis, Massachusetts Institute of Technology.
8. Papoulias, F.A. (1995). Non-linear dynamics and bifurcations in autonomous vehicle guidance and control. In Underwater Robotic Vehicles: Design and Control (Ed. J. Yuh). TST Press, Albuquerque, NM. ISBN 0-6927451-6-2.
9. Khatib, O. (1986). Real time obstacle avoidance for manipulators and mobile robots. International Journal of Robotics Research, 5(1), pp. 90-98.
10. Chuang, J.H. (1998). Potential based modeling of three dimensional workspace for obstacle avoidance. IEEE Transactions on Robotics and Automation, 14(5), pp. 778-785.
11. Fodrea, L.R. (2001). Obstacle avoidance control for the REMUS autonomous underwater vehicle. MSME thesis, Naval Postgraduate School, December. http://www.cs.nps.navy.mil/research/auv/theses/fodrea/Lynn_Fodrea/
12. Ge, S.S. and Y.J. Cui (2000). Dynamic motion planning for mobile robots using potential field method. In Proceedings of the 8th Mediterranean Conference on Control and Automation (MED 2000), Rio, Patras, Greece, 17-19 July.
13. Krogh, B.H. and C.E. Thorpe (1986). Integrated path planning and dynamic steering control for autonomous vehicles. In Proceedings of the 1986 IEEE International Conference on Robotics and Automation, pp. 1664-1669.
14. Lane, D.M., Y. Petillot, and I.T. Ruiz (2001). Underwater vehicle obstacle avoidance and path planning using a multi-beam forward looking sonar. IEEE Journal of Oceanic Engineering, 26(1), pp. 240-251.
15. Latrobe, J.C. (1991). Robot Motion Planning. Kluwer Academic Publishers, Norwell, MA.
16. Stentz, A. (1994). Optimal and efficient path planning for partially-known environments. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '94), vol. 4, pp. 3310-3317.
17. Warren, C.W. (1989). Global path planning using artificial potential fields. In Proceedings of the IEEE Conference on Robotics and Automation, pp. 316-321.