Applications of Nonlinear Analysis pp 581-590 | Cite as
Robots That Do Not Avoid Obstacles
Chapter
First Online:
- 2 Mentions
- 928 Downloads
Abstract
The motion planning problem is a fundamental problem in robotics, so that every autonomous robot should be able to deal with it. A number of solutions have been proposed and a probabilistic one seems to be quite reasonable. However, here we propose a more adoptive solution that uses fuzzy set theory and we expose this solution next to a sort survey on the recent theory of soft robots, for a future qualitative comparison between the two.
Keywords
Motion Planning Problems Soft Robots Path-connected Topological Space Fuzzy Motion Specific Robot Configuration
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
- 1.I. Ashiru, C. Czarnecki, Optimal motion planning for mobile robots using genetic algorithms, in IEEE/IAS International Conference on Industrial Automation and Control, 1995 (I A & C’95) (Cat. No. 95TH8005) (1995), pp. 297–300Google Scholar
- 2.F.E. Browder, Lusternik-schnirelman category and nonlinear elliptic eigenvalue problems. Bull. Am. Math. Soc. 71(4), 644–648 (1965)MathSciNetCrossRefGoogle Scholar
- 3.R. Engelking, General Topology (Heldermann, Berlin, 1989)zbMATHGoogle Scholar
- 4.M. Farber, Topology of robot motion planning, in Morse Theoretic Methods in Nonlinear Analysis and in Symplectic Topology, ed. by P. Biran, O. Cornea, F. Lalonde. NATO Science Series II: Mathematics, Physics and Chemistry, vol. 217 (Springer, Berlin, 2006), pp. 185–230Google Scholar
- 5.Y. Fei, X. Shen, Nonlinear analysis on moving process of soft robots. Nonlinear Dyn. 73(1), 671–677 (2013)MathSciNetCrossRefGoogle Scholar
- 6.D. Georgiou, A. Megaritis, K. Papadopoulos, V. Petropoulos, A study concerning splitting and jointly continuous topologies on C(Y, Z). Sci. Robot. 39(3), 363–379 (2016)MathSciNetGoogle Scholar
- 7.D.F. Jenkins, K.M. Passino, An introduction to nonlinear analysis of fuzzy control systems. J. Intell. Fuzzy Syst. 7, 75–103 (1999)Google Scholar
- 8.C. Laschi, B. Mazzolai, M. Cianchetti, Soft robotics: technologies and systems pushing the boundaries of robot abilities. Sci. Robot. 1(1) (2016). https://doi.org/10.1126/scirobotics.aah3690 CrossRefGoogle Scholar
- 9.J.-C. Latombe, Robot Motion Planning (Springer, New York, 1991)CrossRefGoogle Scholar
- 10.T. Lozano-Pérez, A simple motion-planning algorithm for general robot manipulators. IEEE J. Robot. Autom. 3(3), 224–238 (1987)CrossRefGoogle Scholar
- 11.G. Lupton, J. Scherer, Topological complexity of H-spaces. Proc. Am. Math. Soc. 141(5), 1827–1838 (2013)MathSciNetCrossRefGoogle Scholar
- 12.R.M. May, Simple mathematical models with very complicated dynamics. Nature 261, 459–467 (1976)CrossRefGoogle Scholar
- 13.F. Mei, Z. Man, T. Nguyen, Fuzzy modelling and tracking control of nonlinear systems. Math. Comput. Model. 33(6), 759–770 (2001)CrossRefGoogle Scholar
- 14.S. Sastry, Nonlinear Systems: Analysys, Stability, and Control (Springer, New York, 1999)CrossRefGoogle Scholar
- 15.J.J.E. Slotine, W. Li, Applied Nonlinear Control (Prentice Hall, Englewood Cliffs, 1991), p. 07632Google Scholar
Copyright information
© Springer International Publishing AG, part of Springer Nature 2018