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Dynamic-Domain RRTs: Efficient Exploration by Controlling the Sampling Domain
TLDR
This paper develops and implements a simple new planner which shows significant improvement over existing RRT-based planners and proposes a general framework for minimizing their effect. Expand
Head tracking for the Oculus Rift
TLDR
Methods for efficiently maintaining human head orientation using low-cost MEMS sensors and novel predictive tracking methods that dramatically reduce effective latency (time lag) are presented, which further improves the user experience. Expand
Adaptive tuning of the sampling domain for dynamic-domain RRTs
TLDR
A new variant of the dynamic-domain RRT, which iteratively adapts the sampling domain for the Voronoi region of each node during the search process, which allows automatic tuning of the parameter and significantly increases the robustness of the algorithm. Expand
Generating Uniform Incremental Grids on SO(3) Using the Hopf Fibration
TLDR
This work presents the best-known method to date for constructing incremental, deterministic grids on SO(3), which provides the lowest metric distortion for grid neighbor edges, optimal dispersion-reduction with each additional sample, and explicit neighborhood structure. Expand
Incremental Grid Sampling Strategies in Robotics
TLDR
Algorithms for generating deterministic sample sequences using incremental grid-based sampling to generate dense sample sequences over spaces common in robotics, such as the unit cube, SO(3), and SE(3). Expand
Deterministic sampling methods for spheres and SO(3)
TLDR
An infinite sequence of samples is shown to achieve low-dispersion, which aids in the development of resolution complete algorithms, lattice structure, which allows easy neighbor identification that is comparable to what is obtained for a grid in /spl Ropf//sup d/, and incremental quality, which is similar to that obtained by random sampling. Expand
Generating Uniform Incremental Grids on SO(3) Using the Hopf Fibration
TLDR
This work presents the best-known method to date for constructing incremental, deterministic grids on SO(3), which provides the lowest metric distortion for grid neighbor edges, optimal dispersion-reduction with each additional sample, and explicit neighborhood structure. Expand
Algorithms and Analytic Solutions Using Sparse Residual Dipolar Couplings for High-Resolution Automated Protein Backbone Structure Determination by NMR
TLDR
New algorithms that expand the types and number of RDCs from which analytic solutions are computed and are able to determine high-resolution backbone structures from a limited amount of NMR data are presented. Expand
Improving Motion-Planning Algorithms by Efficient Nearest-Neighbor Searching
TLDR
This paper presents and implements an algorithm for performing NN queries in Cartesian products of R, S1, and RP3, the most common topological spaces in the context of motion planning, and extends the algorithm based on kd-trees, called ANN, developed by Arya and Mount for Euclidean spaces. Expand
Motion Planning for Highly Constrained Spaces
In many motion planing problems, the feasible subspace becomes thin in some directions. This is often due to kinematic closure constraints, which restrict the feasible configurations to aExpand
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