Abstract
The trajectory planning is generally an important and difficult problem to solve when robots are required to do some actions. Robots should move in an efficient way satisfying several constraints imposed on them. The constraints include dynamics of the robots, the limitations of values of state and control variables, e.g. imitations of angles and torques of joints, obstacle avoidance and achievement of required tasks. Our proposed method is based on constraint satisfaction. By using this, the constraints mentioned above can be satisfied effectively and flexibly.
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References
Nakano, T., Nagamatu, M.: A continuous valued neural network with a new evaluation function of degree of unsatisfaction for solving CSP. IEICE, E89-D, 4 (2006)
Shin, K.G., Macky, D.N.: A dynamic programming approach to trajectory planning of robotic manipulators. IEEE Trans. Autom. Control AC-31(6), 450–501 (1986)
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Nagano, S., Fujimoto, Y., Nagamatu, M. (2010). Constraint Satisfaction with Neural Network for Trajectory Planning. In: Hanazawa, A., Miki, T., Horio, K. (eds) Brain-Inspired Information Technology. Studies in Computational Intelligence, vol 266. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04025-2_11
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DOI: https://doi.org/10.1007/978-3-642-04025-2_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04024-5
Online ISBN: 978-3-642-04025-2
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