Masters Thesis: Kinodynamic Steering using Supervised Learning in RRT
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منابع مشابه
Sparse Methods for Efficient Asymptotically Optimal Kinodynamic Planning
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 completeness. SST addresses the limitati...
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This paper proposes a sampling based kinodynamic planning technique for planning persistent monitoring trajectories for a sensing robot in a spatiotemporal environmental field. The robot uses a Kalman-Bucy filter to estimate the spatiotemporal field. Since the error covariance matrix of the Kalman-Bucy filter evolves according to the nonlinear Riccati differential equation, this requires planni...
متن کاملKinodynamic Region Rapidly-exploring Random Trees (KRRRTs)
Kinodynamic motion planning is the problem of finding a collision-free path for a robot under constraints e.g., velocities and accelerations. State of the art techniques rely on sampling-based planning which samples and connects configurations until a valid path is found. Many sampling-based planners have been developed for non-holonomic problems e.g., Kinodynamic Rapidly-exploring Random Trees...
متن کاملAsymptotically Optimal Planning by Feasible Kinodynamic Planning in State-Cost Space
This paper presents an equivalence between feasible kinodynamic planning and optimal kinodynamic planning, in that any optimal planning problem can be transformed into a series of feasible planning problems in a state-cost space whose solutions approach the optimum. This transformation gives rise to a meta-algorithm that produces an asymptotically optimal planner, given any feasible kinodynamic...
متن کاملInformative Trajectory Planning in Spatiotemporal Fields using Kinodynamic RRT*
This paper proposes a sampling based kinodynamic planning technique for planning informative trajectories for a sensing robot in a spatiotemporal environmental field. The robot uses a Kalman-Bucy filter to estimate the spatiotemporal field. The proposed algorithm finds a trajectory for the robot that minimizes a metric on the error covariance matrix of the field estimate. Since the error covari...
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تاریخ انتشار 2017