We present our current progress on the design and analysis of path planning algorithms
based on Rapidlyexploring Random Trees (RRTs). The basis for our methods is the …

Many computer vision techniques infer properties of our physical world from images.
Although images are formed through the physics of light and mechanics, computer vision …

Planning algorithms are impacting technical disciplines and industries around the world,
including robotics, computer-aided design, manufacturing, computer graphics, aerospace …

This paper presents the first randomized approach to kinodynamic planning (also known as
trajectory planning or trajectory design). The task is to determine control inputs to drive a …

In this paper we address the problem of motion planning in the presence of state uncertainty,
also known as planning in belief space. The work is motivated by planning domains …

Abstract Systems that enable high levels of vehicle-automation are now beginning to enter
the commercial marketplace. Road vehicles capable of operating independently of real-time …

Probabilistic inference is the problem of estimating the hidden variables (states or
parameters) of a system in an optimal and consistent fashion as a set of noisy or incomplete …

Planning the path of an autonomous, agile vehicle in a dynamic environment is a very
complex problem, especially when the vehicle is required to use its full maneuvering …

This paper describes the architecture and implementation of an autonomous passenger
vehicle designed to navigate using locally perceived information in preference to potentially …

Problems in the motion control of aircraft are of perennial interest to the control engineer as
they tend to be of complex and nonlinear nature. Modelling and Control of Mini-Flying …