Abstract: "We describe an efficient method for planning in environments for which prior maps are plagued with uncertainty. Our approach processes the map to determine key areas whose uncertainty is crucial to the planning task. It then incorporates the uncertainty associated with these areas using the recently developed PAO* algorithm to produce a fast, robust solution to the original planning task.
Abstract — We introduce a resolution-optimal path planner that considers uncertainty while optimizin...
Abstract—Sampling-based algorithms have dramatically im-proved the state of the art in robotic motio...
In view of the need to adapt to uncertain climate change through spatial interventions, this article...
Reasoning about uncertainty is an essential component of many real-world plan-ning problems, such as...
Attempts to apply classical planning techniques to realistic environments have met with two major d...
Our research area is planning under uncertainty, that is, making sequences of decisions in the face ...
This paper addresses the problem of path planning considering uncertainty criteria over the belief s...
We present experiments studying path planning under spatial uncertainties. In the main experiment, p...
AbstractUncertainty, inherent in most real-world domains, can cause failure of apparently sound clas...
Abstract — In this paper, a two-level path planning algorithm that deals with map uncertainty is pro...
In real-time planning, an agent must select the next action to take within a fixed time bound. Many ...
Abstract — We present a novel approach to mobile robot navigation that enables navigation in outdoor...
Abstract: A model for positional uncertainty in maps with applications in geographical information s...
Planning under uncertainty has been well studied, but usually the uncertainty is in action outcomes....
A planner in the real world must be able to handle uncertainty It must be able to reason about the e...
Abstract — We introduce a resolution-optimal path planner that considers uncertainty while optimizin...
Abstract—Sampling-based algorithms have dramatically im-proved the state of the art in robotic motio...
In view of the need to adapt to uncertain climate change through spatial interventions, this article...
Reasoning about uncertainty is an essential component of many real-world plan-ning problems, such as...
Attempts to apply classical planning techniques to realistic environments have met with two major d...
Our research area is planning under uncertainty, that is, making sequences of decisions in the face ...
This paper addresses the problem of path planning considering uncertainty criteria over the belief s...
We present experiments studying path planning under spatial uncertainties. In the main experiment, p...
AbstractUncertainty, inherent in most real-world domains, can cause failure of apparently sound clas...
Abstract — In this paper, a two-level path planning algorithm that deals with map uncertainty is pro...
In real-time planning, an agent must select the next action to take within a fixed time bound. Many ...
Abstract — We present a novel approach to mobile robot navigation that enables navigation in outdoor...
Abstract: A model for positional uncertainty in maps with applications in geographical information s...
Planning under uncertainty has been well studied, but usually the uncertainty is in action outcomes....
A planner in the real world must be able to handle uncertainty It must be able to reason about the e...
Abstract — We introduce a resolution-optimal path planner that considers uncertainty while optimizin...
Abstract—Sampling-based algorithms have dramatically im-proved the state of the art in robotic motio...
In view of the need to adapt to uncertain climate change through spatial interventions, this article...