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Theoretical sampling
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21	Reusable Sampling-Based Techniques for Manipulation via Pushing Christopher Vo Abstract—In this work, we consider the problem of manipulating a polygonal object through an obstacle-filled environment using only push in Add to Reading List Source URL: iros2011.org Language: English - Date: 2011-09-21 07:00:45 Theoretical computer science Kinodynamic planning International Conference On Intelligent Robots and Systems Partially observable Markov decision process Robot ROS Cognitive robotics Robotics Robot kinematics Motion planning
22	Sampling-based Motion Planning with High-Level Discrete Specifications Erion Plaku Abstract— Motion planning has generally focused on computing a collision-free trajectory to a goal region. Enhancing the ability of rob Add to Reading List Source URL: iros2011.org Language: English - Date: 2011-09-21 07:00:36 Space Discrete space Planning Domain Definition Language Automated planning and scheduling Control theory Applied mathematics Mathematics Motion planning Theoretical computer science
23	Batch Informed Trees (BIT): Sampling-based Optimal Planning via the Heuristically Guided Search of Implicit Random Geometric Graphs arXiv:1405.5848v6 [cs.RO] 26 FebJonathan D. Gammell1 , Siddhartha S. Srinivasa2 Add to Reading List Source URL: www.ri.cmu.edu Language: English* - Date: 2015-05-20 10:11:27 Search algorithms Combinatorial optimization Routing algorithms Rapidly-exploring random tree Robot control Shortest path problem A* search algorithm Graph Connectivity Mathematics Graph theory Theoretical computer science
24	Asymptotic Optimality in Sampling-based Motion Planning Sertac Karaman Although one of the fundamental problems in robotics, the motion planning problem is inherently hard from a computational point of view. In particula Add to Reading List Source URL: iros2011.org Language: English - Date: 2011-09-21 07:00:30 Robot control Search algorithms Rapidly-exploring random tree Motion planning Algorithm Asymptotic computational complexity Asymptotically optimal algorithm Probabilistic roadmap Shortest path problem Applied mathematics Mathematics Theoretical computer science
25	Rapid Sampling for Visualizations with Ordering Guarantees Eric Blais Albert Kim Add to Reading List Source URL: web.engr.illinois.edu Language: English - Date: 2014-10-05 12:02:03 Statistical inference Monte Carlo methods Theoretical computer science Permutations Confidence interval Measurement Sampling Normal distribution Algorithm Statistics Mathematics Probability and statistics
26	The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty Ron Alterovitz Thierry Sim´eon Add to Reading List Source URL: www.ieor.berkeley.edu Language: English - Date: 2007-06-02 12:59:23 Physics Motion planning Theoretical computer science Robotics Probabilistic roadmap Stochastic roadmap simulation Holonomic Stochastic Markov chain Robot control Mathematics Statistics
27	Poisson-RRT Chonhyon Park and Jia Pan and Dinesh Manocha http://gamma.cs.unc.edu/PoissonRRT/ Abstract— We present an RRT-based motion planning algorithm that uses the maximal Poisson-disk sampling scheme. Our approach Add to Reading List Source URL: gamma.cs.unc.edu Language: English - Date: 2014-02-14 21:55:05 Science Theoretical computer science Rapidly-exploring random tree Robot control Image processing Motion planning Siméon Denis Poisson Collision detection Sampling Information science Search algorithms Mathematics
28	The RFDAC (Radio Frequency Digital to Analog Converter) Breakthrough and Advantages Desgning true Nyquist rate DACs that meet theoretical noise and linearity limits is a daunting task, even for the most seasoned designer Add to Reading List Source URL: www.rfcafe.com Language: English - Date: 2015-02-08 22:09:56 Electromagnetism Electronic engineering Electronic circuits Digital-to-analog converter Spurious-free dynamic range Telecommunications Sampling Jitter Baseband Digital signal processing Electronics Signal processing
29	Appendix for “A⇤ Sampling” In this appendix we prove the main theoretical results of the paper and provide additional experimental details. First, define the following shorthand e (g) = exp( g + ) F (g) = exp( exp( Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2014-10-31 17:57:23 Actuarial science Mathematical physics Combinatorics
30	A Taste of Sound Reasoning in Faust Emilio Jesús Gallego Arias, Olivier Hermant, Pierre Jouvelot MINES ParisTech, PSL Research University, France {emilio.gallego_arias, olivier.hermant, pierre.jouvelot}@mines-paristech. Add to Reading List Source URL: www.cri.ensmp.fr Language: English - Date: 2015-03-19 06:05:38 Type theory Functional languages Mathematical logic FAUST Eval Mathematical proof Nyquist–Shannon sampling theorem Coq Dependent type Mathematics Computing Theoretical computer science

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