ObstacleFree

Obstaclefree is a term used in robotics and autonomous navigation to describe a condition in which a robot's intended path or the environment contains no collisions with obstacles.

In planning problems, the free space F is defined as the subset of the configuration space C where the robot does not intersect any obstacle. An obstacle-free path, or obstacle-free trajectory, is a continuous mapping γ: [0,1] → F connecting the start and goal configurations. The goal is to find such a γ that satisfies the robot’s motion constraints and, if present, temporal requirements.

In practice, obstacle-free planning relies on representations such as occupancy grids, voxel maps, or analytic shapes to model obstacles. Problems are formulated for various platforms, including 2D ground robots, 3D aerial vehicles, and robotic arms. Algorithms that produce obstacle-free plans span several families: graph-based planners (A*, Dijkstra), sampling-based planners (RRT, PRM), and optimization-based approaches (CHOMP, TrajOpt). Hybrid methods combine these approaches to improve reliability or speed.

Challenges arise when obstacles are dynamic, sensing is uncertain, or the robot has nonholonomic constraints and complex geometry. Real-time replanning and safety margins are often incorporated to maintain obstacle-freeness under uncertainty, using methods such as model predictive control or probabilistic planning.

See also: obstacle avoidance, free space, motion planning.