AUTHORS: Amir Feizollahi, Rene V. Mayorga
Download as PDF
ABSTRACT: Optimized motion planning of the manipulators with regards to their energy consumption level is a challenging problem in robotics which requires a combination of interdisciplinary studies to offer a solution. In this article, a framework is developed to design a motion planner implementing a proposed search algorithm and simulate the robot motion in different environments. The superiority of the search algorithm is investigated and the development of the MATLAB framework is totally discussed accompanying the simulation results.
KEYWORDS: Motion Planning, Manipulator, Optimization, Graph Search Algorithm, Mathematical Modeling
REFERENCES:
[1] K. S. Senthilkumar and K. K. Bharadwaj, “Multi-robot exploration and terrain coverage in an unknown environment,” Robotics and Autonomous Systems, vol. 60, no. 1, pp. 123– 132, 2012.
[2] K. Nagatani, S. Kiribayashi, Y. Okada, S. Tadokoro, T. Nishimura, T. Yoshida, E. Koyanagi, and Y. Hada, “Redesign of rescue mobile robot Quince,” IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 2011, pp. 13–18.
[3] P. Sabetian, A. Feizollahi, F. Cheraghpour, and S. A. A. Moosavian, “A compound robotic hand with two under-actuated fingers and a continuous finger,” IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 2011, pp. 238–244.
[4] M. Hvilshøj, S. Bøgh, O. S. Nielsen, and O. Madsen, “Autonomous industrial mobile manipulation (AIMM): past, present and future,” Industrial Robot, vol. 39, no. 2, pp. 120–135, 2012.
[5] J. van den Berg, D. Ferguson, and J. Kuffner, “Anytime path planning and replanning in dynamic environments,” IEEE International Conference on Robotics and Automation (ICRA), 2006, pp. 2366–2371.
[6] A. Stentz, “Optimal and efficient path planning for partially-known environments,” IEEE International Conference on Robotics and Automation (ICRA), 1994, pp. 3310–3317.
[7] S. Koenig and M. Likhachev, “D*Lite,” Eighteenth National Conference on Artificial Intelligence, American Association for Artificial Intelligence, 2002, pp. 476–483.
[8] H. Goldstein, Classical mechanics. Pearson Education India, 1965.