Sensitive manipulation

Abstract

This thesis presents an effective alternative to the traditional approach to robotic manipulation. In our approach, manipulation is mainly guided by tactile feedback as opposed to vision. The motivation comes from the fact that manipulating an object implies coming in contact with it, consequently, directly sensing physical contact seems more important than vision to control the interaction of the object and the robot. In this work, the traditional approach of a highly precise arm and vision system controlled by a model-based architecture is replaced by one that uses a low mechanical impedance arm with dense tactile sensing and exploration capabilities run by a behavior-based architecture. The robot OBRERO has been built to implement this approach. New tactile sensing technology has been developed and mounted on the robot's hand. These sensors are biologically inspired and present more adequate features for manipulation than those of state of the art tactile sensors. The robot's limb was built with compliant actuators, which present low mechanical impedance, to make the interaction between the robot and the environment safer than that of a traditional high-stiffness arm. A new actuator was created to fit in the hand size constraints.

(cont.) The reduced precision of OBRERO's limb is compensated by the capability of exploration given by the tactile sensors, actuators and the software architecture. The success of this approach is shown by picking up objects in an unmodelled environment. This task, simple for humans, has been a challenge for robots. The robot can deal with new, unmodelled objects. OBRERO can come gently in contact, explore, lift, and place the object in a different location. It can also detect slippage and external forces acting on an object while it is held. Each one of these steps are done by using tactile feedback. This task can be done with very light objects with no fixtures and on slippery surfaces.