Biologically Inspired Robot Behavior Engineering

1. Evolutionary approaches to neural control of rolling, walking, swimming and flying animats or robots

2. Behavior coordination and its modification on monkey-type mobile robot

3. Visuomotor control in flies and behavior-based agents

4. Using evolutionary methods to parameterize neural models: a study of the lamprey central pattern generator

5. Biologically inspired neural network approaches to real-time collision-free robot motion planning

6. Self-adapting neural networks for mobile robots

7. Evolving robots able to integrate sensory-motor information over time

8. A non-computationally-intensive neurocontroller for autonomous mobile robot navigation

9. Some approaches for reusing behaviour based robot cognitive architectures obtained through evolution

10. Modular neural architectures for robotics

11. Designing neural control architectures for an autonomous robot using vision to solve complex learning tasks

12. Robust estimation of the optical flow based on VQ-BF

13. Steps towards one-shot vision-based self-localization

14. Computing the optimal trajectory of arm movement: the TOPS (Task Optimization in the Presence of Signal-dependent noise) model

15. A general learning approach to visually guided 3D-positioning and pose control of robot arms