Perception and Control for a Humanoid Robot using Vision

This paper provides a summary of our research towards developing a humanoid robot capable of performing interactive manipulation tasks in a domestic/office environment. Visual sensing makes important contributions to all areas of task specification, planning and actuation by enabling the robot to interact through gesture recognition, recognize and locate objects and obstacles, and employ visual feedback for robust control of robotic limbs. An overview of the steps involved in the sensing, planning and actuation of a typical grasping task are described and demonstrated experimentally on our upper-torso humanoid platform. Accurate sensing of range data in a domestic/office environment required the development of a novel laser stripe scanner to overcome the limitations of existing sensors. Our scanner uses stereo measurements to eliminate sensor noise, spurious reflections and cross talk from other robots, and can capture registered colour/range measurements of arbitrary objects in ambient indoor light. Task planning is performed by processing the range data to identify and model objects of interest using simple geometric primitives, and calculating a suitable grasp. Finally, we present a position-based visual servoing framework that provides the robot with automatic hand-eye calibration, allowing accurate and robust placement of the limbs. The fusion of these components allows the humanoid robot to locate and grasp a class of a priori unknown objects in its workspace.