collisionaware

Collisionaware refers to the capability of a system to recognize, assess, and respond to potential collisions in its environment. In robotics, autonomous vehicles, and related fields, a collision-aware system continuously monitors surroundings, predicts possible future trajectories of moving objects, and adjusts its own plan to avoid collisions while pursuing its goals.

Its core elements include sensing, state estimation, and trajectory prediction; and decision making and motion planning with collision constraints. Practical implementations combine sensor data fusion from lidar, radar, cameras, and depth sensors with probabilistic models of motion, time-to-collision calculations, and constraint-based planners such as model predictive control or velocity obstacles. Safe execution requires robust control and contingency behaviors in cases of unexpected disturbances or sensor loss.

Applications span autonomous vehicles, unmanned aerial systems, service robots, and industrial automation, including collaborative robots (cobots) that operate around people, as well as simulation environments used for testing safety properties.

Challenges include handling sensor uncertainty and dynamic, unpredictable agents, achieving real-time performance, coordinating multiple agents, and meeting safety and certification requirements. Research directions focus on integrating learning-based perception with verifiable planning, improving multi-agent collision avoidance, and developing explainable, auditable safety guarantees.

See also: collision avoidance, obstacle avoidance, trajectory planning, safe stopping.