Motion planning is a fundamental research area in robotics. Sampling-based methods offer
an efficient solution for what is otherwise a rather challenging dilemma of path planning …

A defining feature of sampling-based motion planning is the reliance on an implicit
representation of the state space, which is enabled by a set of probing samples …

This paper describes a collection of optimization algorithms for achieving dynamic planning,
control, and state estimation for a bipedal robot designed to operate reliably in complex …

The control of bipedal robotic walking remains a challenging problem in the domains of
computation and experiment, due to the multi-body dynamics and various sources of …

Humanoid robots are complex, dynamic systems. Any humanoid robotic application starts
with determining a sequence of optimal paths to perform a given task in a known or …

The use of mobile robots is growing every day. Path planning algorithms are needed to
allow the coordination of several robots, and make them travel with the least cost and …

Humanoids are preferred over their wheeled counter parts because of their ability to replace
human efforts. Navigation and path planning of humanoids is very much important and …

In this study, two navigational controllers have been developed for the path planning of
single as well as multiple humanoid robots in a cluttered environment using classical and …

We present HPP, a software designed for complex classes of motion planning problems,
such as navigation among movable objects, manipulation, contact-rich multiped locomotion …

Closed kinematic chains are created whenever multiple robot arms concurrently manipulate
a single object. The closed-chain constraint, when coupled with robot joint limits …