Motion planning
Related papers: 20
About
Motion planning is the computational process of determining a valid sequence of configurations or actions that moves a robot from an initial state to a desired goal state while satisfying physical constraints and avoiding obstacles. It operates over a robot's configuration space—a mathematical representation encoding all possible positions and orientations—and must account for the robot's geometry, kinematics, and dynamics alongside environmental structure. In robotics and AI, motion planning underpins nearly every autonomous system: robotic manipulators selecting collision-free joint trajectories, mobile robots navigating cluttered environments, and autonomous vehicles operating in dynamic scenes. Core techniques include artificial potential fields, which attract robots toward goals while repelling them from obstacles; sampling-based methods such as probabilistic roadmaps (PRM) and rapidly-exploring random trees (RRT), which efficiently explore high-dimensional spaces; and optimization-based approaches like CHOMP that refine trajectories for smoothness and safety. Motion planning matters because it bridges high-level task specifications with low-level physical execution, enabling robots to operate reliably and efficiently in complex, real-world environments. Advances in planning algorithms directly expand what autonomous systems can safely accomplish.
Top Researchers
Top Cited Papers
Real-Time Obstacle Avoidance for Manipulators and Mobile Robots
Oussama Khatib
Citations: 7533 • 1986
Probabilistic roadmaps for path planning in high-dimensional configuration spaces
Lydia E. Kavraki, P. Švestka, J.-C. Latombe, M.H. Overmars
Citations: 6256 • 1996
Robot Motion Planning
Jean‐Claude Latombe
Citations: 5429 • 1991
Planning Algorithms
Steven M. LaValle
Citations: 5025 • 2006
Robot Modeling and Control
Mark W. Spong, Seth Hutchinson, M. Vidyasagar
Citations: 3281 • 2006
Randomized Kinodynamic Planning
Steven M. LaValle, James Kuffner
Citations: 3241 • 2001
Robotics: modelling, planning and control
Bruno Siciliano, L. Sciavicco, Luigi Villani, Giuseppe Oriolo
Citations: 2507 • 2009
Principles of Robot Motion: Theory, Algorithms, and Implementations
Howie Choset, Jean‐Claude Latombe
Citations: 2062 • 2005
Motion Planning in Dynamic Environments Using Velocity Obstacles
Paolo Fiorini, Zvi Shiller
Citations: 1930 • 1998
Exact robot navigation using artificial potential functions
Elon Rimon, Daniel E. Koditschek
Citations: 1825 • 1992
Real-time obstacle avoidance for manipulators and mobile robots
Oussama Khatib
Citations: 1684 • 2005
The Open Motion Planning Library
Ioan A. Şucan, Mark Moll, Lydia E. Kavraki
Citations: 1600 • 2012
Real-Time Obstacle Avoidance for Manipulators and Mobile Robots
Oussama Khatib
Citations: 1557 • 1986
A survey on coverage path planning for robotics
Enric Galceran, Marc Carreras
Citations: 1512 • 2013
The complexity of robot motion planning
John Canny
Citations: 1401 • 1988
Sonar-based real-world mapping and navigation
Alberto Elfes
Citations: 1395 • 1987
Optimal and Efficient Path Planning for Partially Known Environments
Anthony Stentz
Citations: 1245 • 1997
Coverage for robotics – A survey of recent results
Howie Choset
Citations: 1189 • 2001
Learning metric-topological maps for indoor mobile robot navigation
Sebastian Thrun
Citations: 1049 • 1998
Minimum-time control of robotic manipulators with geometric path constraints
Kang G. Shin, Neil David McKay
Citations: 992 • 1985