iLab: From Brain to Machine and Back

Autonomous robots with limited computational capacity call for control approaches that generate meaning- ful, goal-directed behavior without using a large amount of resources. The attractor dynamics approach to movement generation is a framework that links sensor data to motor commands via coupled dynamical systems that have attractors at behaviorally desired states. The low computational demands … Read More “Robio2011: Model-free local navigation for humanoid robots” »

The investigation of neuronal accounts of cognition is closely linked to collaboration between behavioral experiments, theory and application and supports the process of moving from pure behaviorist correlation analysis to gaining a real understanding of the underlying mechanisms. Cognition builds upon the individual behavioral history, and  the understanding of cognition is based on neuronal principles. … Read More “BC11: Benefits of ego motion feedback for interactive experiments in virtual reality scenarios” »

The neuronal basis of movement preparation, during which movement parameters such as movement direction are assigned values, is fairly well understood. Motor and premotor cortex as well as portions of parietal cortex represent movement parameters through the activity of neuronal populations. The parameter representation is of dynamic nature, updated in the course of movement and adapts … Read More “BC11: Human like trajectories for humanoid robots” »

Autonomous robots with limited computational capacity call for control approaches that generate meaningful, goal-directed behavior without using a large amount of resources. The attractor dynamics approach to movement generation is a framework that lin…

The movement of autonomous agents in natural environments is restricted by potentially large numbers of constraints. To generate behavior that fulfills all given constraints simultaneously, the attractor dynamics approach to movement generation represe…

  The generation of behavior for autonomous robots in complex environments is restricted by a potentially large number of constraints that must be observed. For many tasks, the relevant constraints can be expressed in a specific, low-dimensional reference frame. The dynamic systems approach to autonomous robotics represents constraints as attractors or repellors over such behaviorally … Read More “Humanoids 2010: Integrating Orientation Constraints Into the Attractor Dynamics Approach for Autonomous Manipulation” »