4 papers
Admissible heuristics for obstacle clearance optimization objectives
Marlin P. Strub, Jonathan D. Gammell
Obstacle clearance in state space is an important optimization objective in path planning because it can result in safe paths. This technical report presents admissible solution- a…
Asymptotically Optimal Sampling-Based Motion Planning Methods
Jonathan D. Gammell, Marlin P. Strub
Motion planning is a fundamental problem in autonomous robotics that requires finding a path to a specified goal that avoids obstacles and takes into account a robot's limitations…
Adaptively Informed Trees (AIT*): Fast Asymptotically Optimal Path Planning through Adaptive Heuristics
Marlin P. Strub, Jonathan D. Gammell
Informed sampling-based planning algorithms exploit problem knowledge for better search performance. This knowledge is often expressed as heuristic estimates of solution cost and u…
Advanced BIT* (ABIT*): Sampling-Based Planning with Advanced Graph-Search Techniques
Marlin P. Strub, Jonathan D. Gammell
Path planning is an active area of research essential for many applications in robotics. Popular techniques include graph-based searches and sampling-based planners. These approach…