Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Genetic Algorithms and Evolution Strategies - Similarities and Differences
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
A Model of Cerebellar Learning for Control of Arm Movements Using Muscle Synergies
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Collada: Sailing the Gulf of 3d Digital Content Creation
Collada: Sailing the Gulf of 3d Digital Content Creation
Comparison of Mechanical Design and Energy Consumption of Adaptable, Passive-compliant Actuators
International Journal of Robotics Research
A Software Platform for Component Based RT-System Development: OpenRTM-Aist
SIMPAR '08 Proceedings of the 1st International Conference on Simulation, Modeling, and Programming for Autonomous Robots
Animals Versus Animats: Or Why Not Model the Real Iguana?
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
PD control with on-line gravity compensation for robots with elastic joints: Theory and experiments
Automatica (Journal of IFAC)
Optimal unsupervised motor learning for dimensionality reduction of nonlinear control systems
IEEE Transactions on Neural Networks
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Anthropomimetic robotics differs from conventional approaches by capitalizing on the replication of the inner structures of the human body, such as muscles, tendons, bones, and joints. Here we present our results of more than three years of research in constructing, simulating, and, most importantly, controlling anthropomimetic robots. We manufactured four physical torsos, each more complex than its predecessor, and developed the tools required to simulate their behavior. Furthermore, six different control approaches, inspired by classical control theory, machine learning, and neuroscience, were developed and evaluated via these simulations or in small-scale setups. While the obtained results are encouraging, we are aware that we have barely exploited the potential of the anthropomimetic design so far. But, with the tools developed, we are confident that this novel approach will contribute to our understanding of morphological computation and human motor control in the future.