International Journal of Robotics Research
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Gait Adaptation in a Quadruped Robot
Autonomous Robots
Novelty detection: a review—part 2: neural network based approaches
Signal Processing
An Approach to Novelty Detection Applied to the Classification of Image Regions
IEEE Transactions on Knowledge and Data Engineering
Controlling bipedal movement using optic flow
Optic flow and beyond
Foot Placement Selection Using Non-geometric Visual Properties
International Journal of Robotics Research
Fast Biped Walking with a Sensor-driven Neuronal Controller and Real-time Online Learning
International Journal of Robotics Research
A Reflexive Neural Network for Dynamic Biped Walking Control
Neural Computation
Gibsonian Affordances for Roboticists
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
A robot leg based on mammalian muscle architecture
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
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The field of biomorphic robotics can advance as quickly as clear principles of biological systems can be identified, implemented, and tested in robotic devices. Here, we describe the implementation of three principles: (1) the prediction of the sensory consequences of movement and its role in the extraction of novelty and awareness; (2) learning affordances and the direct perception of what an agent can do at a particular instant and how it can do it; (3) exploitation of the physical dynamics of a system to simplify robot control.