— The last decade, sampling based planners like the Probabilistic Roadmap Method have proved to be successful in solving complex motion planning problems. We give a reachability ...
Abstract Climbing robots that climb flat structures using suction cups or magnets are commonly described in the literature. However, robots that can autonomously find randomly plac...
— Affordances represent the behavior of objects in terms of the robot’s motor and perceptual skills. This type of knowledge plays a crucial role in developmental robotic system...
Luis Montesano, Manuel Lopes, Alexandre Bernardino...
— We present a probabilistic architecture for solving generically the problem of extracting the task constraints through a Programming by Demonstration (PbD) framework and for ge...
Abstract— Randomized motion planning techniques are responsible for many of the recent successes in robot control. However, most motion planning algorithms assume perfect and com...