A new motion planning method for robots in static workspaces is presented. This method
proceeds in two phases: a learning phase and a query phase. In the learning phase, a …

Probabilistic roadmap planners (PRMs) form a relatively new technique for motion planning
that has shown great potential. A critical aspect of PRM is the probabilistic strategy used to …

For a number of common configurations of points (lines) in the plane, we develop data
structures in which insertions and deletions of points (or lines, respectively) can be processed …

In numerous computer applications there is a need of storing large sets of objects in such a
way that some questions about those objects can be answered efficiently. Data structures …

There are many problems in computational geometry for which the best know algorithms take
time Θ(n 2 ) (or more) in the worst case while only very low lower bounds are known. In this …

The probabilistic roadmap approach is one of the leading motion planning techniques. Over
the past eight years the technique has been studied by many different researchers. This has …

We present a new approach to the multi-robot path planning problem, where a number of
robots are to change their positions through feasible motions in the same static environment. …

In this paper we address the problem of motion planning for multiple robots. We introduce a
prioritized method, based on a powerful method for motion planning in dynamic …

We present a new local method for collision avoidance that is based on collision prediction.
In our model, each pedestrian predicts possible future collisions with other pedestrians and …

Many algorithms have been proposed that create a path for a robot in an environment with
obstacles. Most methods are aimed at finding a solution. However, for many applications, the …