Zakary Littlefield

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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 computational(More)
Abstract. This work describes STABLE SPARSE RRT (SST), an algorithm that (a) provably provides asymptotic (near-)optimality for kinodynamic planning without access to a steering function, (b) maintains only a sparse set of samples, (c) converges fast to high-quality paths and (d) achieves competitive running time to RRT, which provides only probabilistic(More)
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)
Many methods for planning under uncertainty operate in the belief space, i.e., the set of distributions over states. Although the problem is computationally hard, recent advances have shown that belief-space planning is becoming practical for many medium size problems. Some of the most successful methods utilize sampling and often rely on distances between(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)
This paper studies two end-effector modalities for warehouse picking: (i) a recently developed, underactuated three-finger hand and (ii) a custom built, vacuum-based gripper. The two systems differ on how they pick objects. The first tool provides increased flexibility, while the vacuum alternative is simpler and smaller. The aim is to show how the(More)
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