Zakary Littlefield

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Sampling-based algorithms are viewed as practical solutions for high-dimensional motion planning. Recent progress has taken advantage of random geometric graph theory to show how asymptotic optimality can also be achieved with these methods. Achieving this desirable property for systems with dynamics requires solving a two-point boundary value problem (BVP)(More)
— Recent motion planners, such as RRT * , that achieve asymptotic optimality require a local planner, which connects two states with a trajectory. For systems with dynamics , the local planner corresponds to a two-point boundary value problem (BVP) solver, which is not always available. Furthermore, asymptotically optimal solutions tend to increase(More)
This paper describes a software infrastructure for developing controllers and planners for robotic systems, referred here as PRACSYS. At the core of the software is the abstraction of a dynamical system, which, given a control, propagates its state forward in time. The platform simplifies the development of new controllers and planners and provides an(More)
This paper describes a software infrastructure for developing and composing task and motion planners. The functionality of motion planners is well defined and they provide a basic primitive on top of which it is possible to develop planners for addressing higher level tasks. It is more challenging, however, to identify a common interface for task planners,(More)
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