Abstract
The dynamical systems approach and recurrent neural control provides a rich foundation for the generation of natural behaviors on autonomous robots because the environment, the robot, and control systems are regarded as a single dynamical system. Robot behaviors can thus be shaped as attractors of this dynamical system. Within this framework, sensorimotor loops for walking and keeping balance have been realized on the Myon robot. Different behaviors can be shaped as co-existing attractors which allows for smooth and reliable switching between them. We introduce the concept of Cognitive Sensorimotor Loops (CSLs) as well as the use of quadrics and discuss their benefits for behavior control. The presentation of every technique is accompanied by a real world example using humanoid robots. Finally, a grasping motion is developed using the same methods.
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References
Collins SH (2005) A Bipedal Walking Robot with Efficient and Human-Like Gait. In: Proceedings of IEEE International Conference on Robotics and Automation
Hild M, Kubisch M (2011) Self-Exploration of Autonomous Robots Using Attractor-Based Behavior Control and ABC-Learning. In: Proceedings of the 11th Scandinavian Conference on Artificial Intelligence, Trondheim, Norway
Hild M, Kubisch M, Gohring D (2007) How to Get from Interpolated Keyframes to Neural Attractor Landscapes – and Why. In: Proceedings of the 3rd European Conference on Mobile Robots, Freiburg, Germany
Hild M, Kubisch M, Hofer S (2011a) Using Quadric-Representing Neurons (QRENs) for Real-Time Learning of an Implicit Body Model During Autonomous Self-Exploration. In: Robotica 2011, Lisbon, Portugal
Hild M, Siedel T, Benckendorff C, Kubisch M, Thiele C (2011b) Myon: Concepts and Design of a Modular Humanoid Robot Which Can Be Reassembled During
Runtime. In: Proceedings of the 14th Int. Conf. on Climbing andWalking Robots
Johansson RS, Westling G, Backstrom A, Flanagan JR (2001) Eye-Hand Coordination in Object Manipulation. The Journal of Neuroscience pp 6917–6932
Kalaska JF (2007) From Intention to Action: Motor Cortex and the Control of Reaching. In: Progress in Motor Control, A Multidisciplinary Perspective
Kubisch M, Hild M, Hofer S (2010) Proposal of an Intrinsically Motivated System for Exploration of Sensorimotor State Spaces. In: Proceedings of the 10th International Conference on Epigenetic Robotics, Orenas Slott, Sweden
Kubisch M, Benckendorff C, Hild M (2011a) Balance Recovery of a Humanoid
Robot Using Cognitive Sensorimotor Loops (CSLs). In: Proceedings of the 14th International Conference on Climbing and Walking Robots
Kubisch M, Werner B, Hild M (2011b) Using Co-Existing Attractors of a Sensorimotor Loop for the Motion Control of a Humanoid Robot. In: International Conference on Neural Computation Theory and Applications
Pasemann F, Hild M, Zahedi K (2003) SO(2)-Networks as Neural Oscillators. Proc of Int Work-Conf on Artificial and Natural Neural Networks pp 144 – 151
Pollaccia G (2001) Road Signs Recognition Using a Dynamic Pixel Aggregation Technique in the HSV Color Space. In: Proceedings of the 11th International Conference on Image Analysis and Processing
Popovic DB, Sinkjaer T (2003) Control of Movement for the Physically Disabled. Center for Sensory-Motor Interaction
Sarlegna F, Saintburg R (2007) The Roles of Vision and Proprioception in the Planning Reaching Movements. In: Progress in Motor Control, A Multidisciplinary Perspective, Springer Schneider A (2006) Local Positive Velocity Feedback for the Movement Control of Elastic Joints in Closed Kinematic Chains: A Modelling and Simulation Study of a 2DoF Arm and a 3D oF Insect Leg. Dissertation
Solomon JH, Wisse M, Hartmann MJ (2010) Fully Interconnected, Linear Control for Limit Cycle Walking. Adaptive Behavior 18
Thompson JMT, Stewart HB (1986) Nonlinear Dynamics and Chaos. Wiley, U.K.
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Kubisch, M., Benckendorff, C., Werner, B., Bethge, S., Hild, M. (2012). Neural Implementation of Behavior Control. In: Steels, L., Hild, M. (eds) Language Grounding in Robots. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-3064-3_3
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DOI: https://doi.org/10.1007/978-1-4614-3064-3_3
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