Adaptive Neural Networks and Robot Intelligent Control in Direct or Indirect Interaction with Humans offers a particular methodology for using neural networks to solve control problems of nonlinear systems interacting directly (mobile robot exoskeleton type) or indirectly with humans (redundant robot manipulators serial or parallel). In addition, the book provides novel perspectives and research ideas for further strengthening the presence of humans in the control loop (intention, thought, etc.). The robots used for illustration purposes were designed in collaboration with industry.
- Offers a methodology for using neural networks to solve control problems of nonlinear systems interacting directly or indirectly with humans
- Provides novel perspectives and research ideas for further strengthening the presence of humans in the control loop
Table of Contents
1. Neural Network Layers 2. Robot Manipulators and Redundancy 3. Portable Robots and Support 4. Adaptive Neural Control of Redundant Robots with Obstacle Avoidance 5. Control Force / Position of Parallel Robots 6. Control Mobile Robots 7. Towards Neuronal Control
