Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Dynamical systems for the behavioral organization of an anthropomorphic mobile robot
Proceedings of the fifth international conference on simulation of adaptive behavior on From animals to animats 5
Robot arm control exploiting natural dynamics
Robot arm control exploiting natural dynamics
Mathematical Programming: Series A and B
Experiments and models of sensorimotor interactions during locomotion
Biological Cybernetics - Special Issue: Dynamic Principles
Adaptive Dynamic Walking of a Quadruped Robot on Natural Ground Based on Biological Concepts
International Journal of Robotics Research
Towards long-lived robot genes
Robotics and Autonomous Systems
Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction
Reaching with multi-referential dynamical systems
Autonomous Robots
Self-organized adaptive legged locomotion in a compliant quadruped robot
Autonomous Robots
Learning and generalization of motor skills by learning from demonstration
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Task-space trajectories via cubic spline optimization
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Temporal stabilization of discrete movement in variable environments: an attractor dynamics approach
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Roombots: reconfigurable robots for adaptive furniture
IEEE Computational Intelligence Magazine
Modeling discrete and rhythmic movements through motor primitives: a review
Biological Cybernetics
Task-specific generalization of discrete and periodic dynamic movement primitives
IEEE Transactions on Robotics
Biologically inspired layered learning in humanoid robots
Knowledge-Based Systems
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Vertebrates are able to quickly adapt to new environments in a very robust, seemingly effortless way. To explain both this adaptivity and robustness, a very promising perspective in neurosciences is the modular approach to movement generation: Movements results from combinations of a finite set of stable motor primitives organized at the spinal level. In this article we apply this concept of modular generation of movements to the control of robots with a high number of degrees of freedom, an issue that is challenging notably because planning complex, multidimensional trajectories in time-varying environments is a laborious and costly process. We thus propose to decrease the complexity of the planning phase through the use of a combination of discrete and rhythmic motor primitives, leading to the decoupling of the planning phase (i.e. the choice of behavior) and the actual trajectory generation. Such implementation eases the control of, and the switch between, different behaviors by reducing the dimensionality of the high-level commands. Moreover, since the motor primitives are generated by dynamical systems, the trajectories can be smoothly modulated, either by high-level commands to change the current behavior or by sensory feedback information to adapt to environmental constraints. In order to show the generality of our approach, we apply the framework to interactive drumming and infant crawling in a humanoid robot. These experiments illustrate the simplicity of the control architecture in terms of planning, the integration of different types of feedback (vision and contact) and the capacity of autonomously switching between different behaviors (crawling and simple reaching).