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 …

Path planning and trajectory planning are crucial issues in the field of Robotics and, more
generally, in the field of Automation. Indeed, the trend for robots and automatic machines is …

Realistic manipulation tasks require a robot to interact with an environment with a prolonged
sequence of motor actions. While deep reinforcement learning methods have recently …

During the last decade, sampling-based algorithms for path planning have gained
considerable attention. The RRT*, a variant of RRT (rapidly-exploring random trees), is of …

Contact is at the core of robotic manipulation. At times, it is desired (eg manipulation and
grasping), and at times, it is harmful (eg when avoiding obstacles). However, traditional path …

Planning algorithms are impacting technical disciplines and industries around the world,
including robotics, computer-aided design, manufacturing, computer graphics, aerospace …

A simple and efficient randomized algorithm is presented for solving single-query path
planning problems in high-dimensional configuration spaces. The method works by …

This paper presents the first randomized approach to kinodynamic planning (also known as
trajectory planning or trajectory design). The task is to determine control inputs to drive a …

We present our current progress on the design and analysis of path planning algorithms
based on Rapidlyexploring Random Trees (RRTs). The basis for our methods is the …

Describes an approach to probabilistic roadmap planners (PRMs). The overall theme of the
algorithm, called Lazy PRM, is to minimize the number of collision checks performed during …