One of the primary challenges for autonomous robotics in uncertain and dynamic
environments is planning and executing a collision-free path. Hybrid dynamic obstacles …

Highly dynamic environments pose a particular challenge for motion planning due to the
need for constant evaluation or validation of plans. However, due to the wide range of …

This paper presents a real-time path planning algorithm that guarantees probabilistic
feasibility for autonomous robots with uncertain dynamics operating amidst one or more …

Algorithms for motion planning in unknown environments are generally limited in their ability
to reason about the structure of the unobserved environment. As such, current methods …

To operate with limited sensor horizons in unpredictable environments, autonomous robots
use a receding-horizon strategy to plan trajectories, wherein they execute a short plan while …

Mobile robots often must find a trajectory to another position in their environment, subject to
constraints. This is the problem of planning a path through a continuous domain Rapidly …

A new real-time obstacle avoidance method for mobile robots has been developed and
implemented. This metho. d, named the vector field histogram (VFH), permits the detection of …

This paper presents a novel optimization-based path planner that is capable of planning
multiple contingency paths to directly account for uncertainties in the future trajectories of …

Collision avoidance in aerial environments using the conventional artificial potential field
(APF) often faces local minima problems and the results prevent unmanned aerial vehicles …

Probabilistic roadmap (PRM) planners have been successful in path planning of robots with
many degrees of freedom, but sampling narrow passages in a robot's configuration space …