Integrating Perception & Planning for Humanoid Autonomy
Philipp Michel
Robotics Institute
Carnegie Mellon University
Abstract:
This thesis explores appropriate approaches to perception on humanoids and ways of coupling sensing and planning to generate navigation and manipulation strategies that can be executed reliably.
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We examine how predictive information about the future state of the world gathered from observation enables navigation in the presence of challenging moving obstacles. We show how programmable graphics hardware can be exploited to create a novel, model-based 3D tracking system able to robustly address the difficulties of real-time sensing specifically encountered on a locomoting humanoid. This thesis argues furthermore that reliability of autonomous operation can be improved by reasoning about perception during the planning process, rather than maintaining the traditional separation of the sensing and planning stages.
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