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 …

Sampling-based motion planning is one of the fundamental paradigms to generate robot
motions, and a cornerstone of robotics research. This comparative review provides an up-to …

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

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 …

Now in its third edition, this textbook is a comprehensive introduction to the multidisciplinary
field of mobile robotics, which lies at the intersection of artificial intelligence, computational …

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 …

Planning the path of an autonomous, agile vehicle in a dynamic environment is a very
complex problem, especially when the vehicle is required to use its full maneuvering …

This paper presents a novel randomized motion planner for robots that must achieve a
specified goal under kinematic and/or dynamic motion constraints while avoiding collision …

We present, implement, and analyze a spectrum of closely-related planners, designed to
gain insight into the relationship between classical grid search and probabilistic roadmaps …

Probabilistic roadmap planners (PRMs) form a relatively new technique for motion planning
that has shown great potential. A critical aspect of PRM is the probabilistic strategy used to …