We propose a combination of techniques that solve multiple queries for motion planning problems with single query planners. Our implementation uses a probabilistic roadmap method (PRM) with bidirectional rapidly exploring random trees (BI-RRT) as the local planner. With small modifications to the standard algorithms, we obtain a multiple query planner which is significantly faster and more reli...

We present a new approach for motion planning and maintainability studies in complex 3D CAD environments. It automatically computes a collision-free path for moving objects among stationary and completely known obstacles. Our framework uses a combination of analytic, criticalitybased and probabilistic techniques to compute the path. It starts with an global strategy, which uses an approximate V...

We consider the problem of on-line continual planning, in which additional goals may arrive while plans for previous goals are still executing and plan quality depends on how quickly goals are achieved. This is a challenging problem even in domains with deterministic actions. One common and straightforward approach is reactive planning, in which plans are synthesized when a new goal arrives. In...

In this work, we have developed a real-time camera control module for navigation in virtual environments. With this module, the tracking motion of a third-person camera can be generated automatically to allow a user to focus on the control of an avatar. The core of this module consists of a motion planner that uses the probabilistic roadmap method and a lazy update strategy to generate the moti...

We introduce an approach to high-level conditional planning we call-safe planning. This probabilistic approach commits us to planning to meet some speciied goal with a probability of success of at least 1 ? for some user-supplied. We describe several algorithms for-safe planning based on conditional planners. The two conditional planners we discuss are Peot and Smith's non-linear conditional pl...

Weaver is a hybrid planning algorithm that can create plans in domains that include uncertainty, modelled either as incomplete knowledge of the initial state of the world, of the effects of plan steps or of the possible external events. The plans are guaranteed to exceed some given threshold probability of success. Weaver creates a Bayesian network representation of a plan to evaluate it, in wh...

This paper addresses the problem of path planning for a thin elastic metal plate under fairly general manipulation constraints. The underlying geometric model for the plate is provided by a B ezier representation. The geometric model is augmented by a realistic mechanical model. We assume that the plate is manipulated in accordance with a set of user-deened grasping constraints that specify the...

This paper presents a technique for motion planning which is capable of planning trajectories for a large number of nonholonomic robots. The robots plan within a two dimensional environment that consists of stationary/moving obstacles, and fixed boundaries. Each robot uses randomized motion planner techniques based on Probabilistic Road Maps (PRM’s) to construct it’s own trajectory that is free...

In this paper we will describe a software package , called DT-Planner, able to represent and solve nite-state Markov Decision Processes, by exploiting a novel graphical formalism, called Innuence View. An Innuence View is a directed acyclic graph that depicts the probabilistic relationships between the problems state variables in a generic time transition ; additional variables, called event va...