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Metaheuristics for Robotics [Kõva köide]

(Assystem Technologies, France), (University of Paris 8, France), (University of Paris-Est Créteil, France)
  • Formaat: Hardback, 184 pages, kõrgus x laius x paksus: 239x163x15 mm, kaal: 408 g
  • Ilmumisaeg: 14-Feb-2020
  • Kirjastus: ISTE Ltd and John Wiley & Sons Inc
  • ISBN-10: 1786303809
  • ISBN-13: 9781786303806
Teised raamatud teemal:
Metaheuristics for RoboticsSuurem pilt
  • Formaat: Hardback, 184 pages, kõrgus x laius x paksus: 239x163x15 mm, kaal: 408 g
  • Ilmumisaeg: 14-Feb-2020
  • Kirjastus: ISTE Ltd and John Wiley & Sons Inc
  • ISBN-10: 1786303809
  • ISBN-13: 9781786303806
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781786303806.html
Märksõnad:
This book is dedicated to the application of metaheuristic optimization in trajectory generation and control issues in robotics. In this area, as in other fields of application, the algorithmic tools addressed do not require a comprehensive list of eligible solutions to effectively solve an optimization problem. This book investigates how, by reformulating the problems to be solved, it is possible to obtain results by means of metaheuristics.





Through concrete examples and case studies – particularly related to robotics – this book outlines the essentials of what is needed to reformulate control laws into concrete optimization data.





The resolution approaches implemented – as well as the results obtained – are described in detail, in order to give, as much as possible, an idea of metaheuristics and their performance within the context of their application to robotics.
Preface ix
Introduction xiii
Chapter 1 Optimization: Theoretical Foundations and Methods
1(26)
1.1 The formalization of an optimization problem
1(4)
1.2 Constrained optimization methods
5(10)
1.2.1 The method of Lagrange multipliers
9(2)
1.2.2 Method of the quadratic penalization
11(1)
1.2.3 Methods of interior penalties
12(1)
1.2.4 Methods of exterior penalties
13(1)
1.2.5 Augmented Lagrangian method
14(1)
1.3 Classification of optimization methods
15(6)
1.3.1 Deterministic methods
16(2)
1.3.2 Stochastic methods
18(3)
1.4 Conclusion
21(1)
1.5 Bibliography
22(5)
Chapter 2 Metaheuristics for Robotics
27(26)
2.1 Introduction
27(1)
2.2 Metaheuristics for trajectory planning problems
28(17)
2.2.1 Path planning
29(14)
2.2.2 Trajectory generation
43(2)
2.3 Metaheuristics for automatic control problems
45(5)
2.4 Conclusion
50(1)
2.5 Bibliography
50(3)
Chapter 3 Metaheuristics for Constrained and Unconstrained Trajectory Planning
53(34)
3.1 Introduction
53(1)
3.2 Obstacle avoidance
54(4)
3.3 Bilevel optimization problem
58(1)
3.4 Formulation of the trajectory planning problem
59(4)
3.4.1 Objective functions
60(2)
3.4.2 Constraints
62(1)
3.5 Resolution with a bigenetic algorithm
63(3)
3.6 Simulation with the model of the Neuromate robot
66(17)
3.6.1 Geometric model of the Neuromate robot
67(4)
3.6.2 Kinematic model of the Neuromate robot
71(1)
3.6.3 Simulation results
72(11)
3.7 Conclusion
83(1)
3.8 Bibliography
83(4)
Chapter 4 Metaheuristics for Trajectory Generation by Polynomial Interpolation
87(34)
4.1 Introduction
87(1)
4.2 Description of the problem addressed
88(3)
4.3 Formalization
91(3)
4.3.1 Criteria
91(1)
4.3.2 Constraints
92(2)
4.4 Resolution
94(6)
4.4.1 Augmented Lagrangian
95(2)
4.4.2 Genetic operators
97(2)
4.4.3 Solution coding
99(1)
4.5 Simulation results
100(16)
4.6 Conclusion
116(2)
4.7 Bibliography
118(3)
Chapter 5 Particle Swarm Optimization for Exoskeleton Control
121(26)
5.1 Introduction
121(2)
5.2 The system and the problem under consideration
123(3)
5.2.1 Representation and model of the system under consideration
123(2)
5.2.2 The problem under consideration
125(1)
5.3 Proposed control algorithm
126(9)
5.3.1 The standard PSO algorithm
126(2)
5.3.2 Proposed control approach
128(7)
5.4 Experimental results
135(7)
5.5 Conclusion
142(1)
5.6 Bibliography
143(4)
Conclusion 147(6)
Index 153
Hamouche Oulhadj is an Associate Professor at the University of Paris-Est Créteil, France. He is an Engineer in Electrical Engineering and has a PhD in Biomedical Engineering. His main research interests are in optimization, pattern recognition and image processing.

Boubaker Daachi is a Full Professor in Computer Science at the University of Paris 8, France. He is an Engineer in Computer Science and has a PhD in Robotics. His main research interests are in brain computer interfaces, biometrics, neurofeedback and robotics.

Riad Menasri is a Development Engineer at Assystem Technologies, France. Holding a Master's degree in Advanced Systems and Robotics and a PhD in Robotics, his main research interests are in optimization and trajectory planning for robotics applications.