Three-Dimensional Obstacle Avoidance of Blimp-Type Unmanned Aerial Vehicle Flying in Unknown and Non-Uniform Wind Disturbance
NTT Corporation, NTT Communication Science Laboratories, 3-1 Wakamiya, Morinosato, Atsugi, Kanagawa 243-0198, Japan
A blimp-type unmanned aerial vehicle (BUAV) maintains its longitudinal motion using buoyancy provided by the air around it. This means the density of a BUAV equals that of the surrounding air. Because of this, the motion of a BUAV is seriously affected by flow disturbances, whose distribution is usually non-uniform and unknown. In addition, the inertia in the heading motion is very large. There is also a strict limitation on the weight of equipment in a BUAV, so most BUAVs are so-called under-actuated robots. From this situation, it can be said that the motion planning of the BUAV considering the stochastic property of the disturbance is needed for obstacle avoidance. In this paper, we propose an approach to the motion planning of a BUAV via the application of Markov decision process (MDP). The proposed approach consists of a method to prepare a discrete MDP model of the BUAV motion and a method to maintain the effect of the unknown wind on the BUAV’s motion. A dynamical simulation of a BUAV in an environment with wind disturbance shows high performance of the proposed method.
-  T. Fukao, K. Fujitani, and T. Kanade, “An Autonomous Blimp for a Surveyllance System,” Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1820-1825, October, 2003.
-  J. P. Laumond, P. Jacobs, M. Taix, and R. Murray, “A motion planner for nonholonomic mobile robots,” IEEE Transactions on Robotics and Automation, Vol.10, No.5, pp. 577-593, 1994.
-  T. Yamasaki and N. Goto, “Identification of Blimp Dynamics by Flight Tests,” Transactions of JSASS, Vol.43, pp. 195-205, 2003.
-  D. R. Yoerger and J.-J. E. Slotine, “Adaptive sliding control of an experimental underwater vehicle,” Proceedings of 1991 IEEE International Conference on Robotics and Automation, pp. 2746-2751, April, 1991.
-  K. Kim and T. Ura, “Fuel-Optimal Guidance and Tracking Control of AUV under Current Interaction,” Proceedings of ISOPE 2003, pp. 191-196, May, 2003.
-  H. Kawano, “Method for Applying Reinforcement Learning to Motion Planning and Control of Under-actuated Underwater Vehicle in Unknown Non-uniform Sea flow,” Proceedings of 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 146-152, August, 2005.
-  H. Kimura and S. Kobayashi, “Efficient Non-Linear Control by Combining Q-learning with Local Linear Controllers,” Proceedings of 16th International Conference on Machine Learning, pp. 210-219, June, 1999.
-  R. S. Sutton and A. G. Barto, “Reinforcement Learning: An Introduction,” MIT Press, 1998.
-  B. L. Paris, “Modeling Turbulence For Flight Simulation at NASAAMES,” CSCR, No.4, January, 1975.
-  M. Aicardi, G. Casalino, and G. Indiveri, “New techniques for the guidance of underactuated marine vehicles,” Proceedings of the IARP Workshop, pp. 88-98, October, 2001.
-  M. Venditteli and J. P. Laumond, “Obstacle Distance for Car-like Robots,” IEEE Transactions on Robotics and Automation, Vol.15, No.4, pp. 678-691, 1999.
-  M. Yamada and M. Tomizuka, “Robust Global Exponential Stabilization of an Underactuated Airship,” Proceedings of the IFAC World Congress, Prague, Czech Republic, Mo-A02-To-5, 2005.
-  H. Kawano and T. Ura, “Motion Planning Algorithm for Non-Holonomic Autonomous Underwater Vehicle in Disturbance using Reinforcement Learning and Teaching Method,” Proceedings of IEEE International Conference on Robotics and Automation, pp. 4032-4038, May, 2002.
-  H. Kawano and T. Ura, “Fast Reinforcement Learning Algorithm for Motion Planning of Non-Holonomic Autonomous Underwater Vehicle in Disturbance,” Proceedings of 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 903-908, October, 2002.
-  S. Koenig and M. Likhachev, “Improved Fast Replanning for Robot Navigation in Unknown Terrain,” Proceedings of the 2002 IEEE International Conference on Robotics and Automation, pp. 968-975, May, 2002.
-  E. S. Jang, S. Jung, and T. C. Hsia, “Collision Avoidance of a Mobile Robot for Moving Obstacles Based on Impedance Force Control Algorithm,” Proceedings of 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 277-282, August, 2005.
-  E. P. Lopes, E. P. L. Aude, J. T. C. Silveira, H. Serderia, and M. F. Martins, “Application of a Blind Person Strategy for Obstacle Avoidance with the use of Potential Fields,” Proceedings of 2001 IEEE International Conference on Robotics and Automation, pp. 2911-2916, May, 2001.
-  K. Ishii, T. Fujii, and T. Ura, “An on-line adaptation method in a neural network based control system for AUVs,” IEEE Journal of Oceanic Engineering, Vol.20, No.3, pp. 221-228, July, 1995.
-  R. A. Brooks, “A robust layered control system for a mobile robot,” IEEE Journal of Robotics and Automation, RA-2, pp. 14-23, 1986.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.
Copyright© 2007 by Fuji Technology Press Ltd. and Japan Society of Mechanical Engineers. All right reserved.