09-10-2010, 10:52 AM
CHALLENGES FOR ROBOT MANIPULATION INHUMAN ENVIRONMENT.ppt (Size: 761 KB / Downloads: 117)
This article is presented by:
RAJESH KUMAR.M
CHALLENGES FOR ROBOT MANIPULATION IN HUMAN ENVIRONMENT
Within factories around the world, robots perform heroic feats of manipulation on a daily basis. They lift massive objects, move with blurring speed, and repeat complex performances with unerring precision. Yet outside of carefully controlled settings, even the most sophisticated robot would be unable to get you a glass of water. The everyday manipulation tasks we take for granted would stump the greatest robot bodies and brains in existence today.
To what End
Commercially available robotic toys and vacuum cleaners inhabit our living spaces, and robotic vehicles have raced across the desert. These successes appear to foreshadow an explosion of robotic applications in our daily lives, but without advances in robot manipulation, many promising robotic applications will not be possible. Whether in a domestic setting or the work-place, we would like robots to physically alter the world through contact.
Today’s robots
To date, robots have been very successful at manipulation in simulation and controlled environments such as a factory. Outside of controlled environments, robots have only performed sophisticated manipulation tasks when operated by a human.
Simulation:-
Within simulation, robots have performed sophisticated manipulation tasks such as grasping convoluted objects, tying knots, and carrying objects around complex obstacles. The control algorithms for these demonstrations often employ search algorithms to find satisfactory solutions, such as a path to a goal state, or a set of contact points that maximize a measure of grasp quality. For example, many virtual robots use algorithms for motion planning that rapidly search for paths through a state space that models the kinematics and dynamics of the world . Most of these simulations ignore the robot’s sensory systems and assume that the state of the world is known with certainty. For example, they often assume that the robot knows the three-dimensional (3-D) structure of the objects it is manipulating.