Algorithmic Foundations of Robotics IX

1. Front Matter

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2. Session I

   1. Homotopic Path Planning on Manifolds for Cabled Mobile Robots

      • Takeo Igarashi, Mike Stilman

      Pages 1-18

   2. An Equivalence Relation for Local Path Sets

      • Ross A. Knepper, Siddhartha S. Srinivasa, Matthew T. Mason

      Pages 19-35

   3. Using Lie Group Symmetries for Fast Corrective Motion Planning

      • Konstantin Seiler, Surya P. N. Singh, Hugh Durrant-Whyte

      Pages 37-52

   4. Asynchronous Distributed Motion Planning with Safety Guarantees under Second-Order Dynamics

      • Devin K. Grady, Kostas E. Bekris, Lydia E. Kavraki

      Pages 53-70

3. Session II

   1. Incremental Sampling-Based Algorithms for a Class of Pursuit-Evasion Games

      • Sertac Karaman, Emilio Frazzoli

      Pages 71-87

   2. Multiagent Pursuit Evasion, or Playing Kabaddi

      • Kyle Klein, Subhash Suri

      Pages 89-104

   3. Reconfiguring Chain-Type Modular Robots Based on the Carpenter’s Rule Theorem

      • Jungwon Seo, Steven Gray, Vijay Kumar, Mark Yim

      Pages 105-120

   4. Robomotion: Scalable, Physically Stable Locomotion for Self-reconfigurable Robots

      • Sam Slee, John Reif

      Pages 121-137

4. Session III

   1. Adaptive Time Stepping in Real-Time Motion Planning

      • Kris Hauser

      Pages 139-155

   2. The Bayes Tree: An Algorithmic Foundation for Probabilistic Robot Mapping

      • Michael Kaess, Viorela Ila, Richard Roberts, Frank Dellaert

      Pages 157-173

   3. Monte Carlo Value Iteration for Continuous-State POMDPs

      • Haoyu Bai, David Hsu, Wee Sun Lee, Vien A. Ngo

      Pages 175-191

   4. Randomized Belief-Space Replanning in Partially-Observable Continuous Spaces

      • Kris Hauser

      Pages 193-209

5. Session IV

   1. GPU-Based Parallel Collision Detection for Real-Time Motion Planning

      • Jia Pan, Dinesh Manocha

      Pages 211-228

   2. CCQ: Efficient Local Planning Using Connection Collision Query

      • Min Tang, Young J. Kim, Dinesh Manocha

      Pages 229-247

   3. Modeling Contact Friction and Joint Friction in Dynamic Robotic Simulation Using the Principle of Maximum Dissipation

      • Evan Drumwright, Dylan A. Shell

      Pages 249-266

   4. Energy-Based Modeling of Tangential Compliance in 3-Dimensional Impact

      • Yan-Bin Jia

      Pages 267-284

6. Session V

   1. Sampling-Diagram Automata: A Tool for Analyzing Path Quality in Tree Planners

      • Oren Nechushtan, Barak Raveh, Dan Halperin

      Pages 285-301

   2. Sufficient Conditions for the Existence of Resolution Complete Planning Algorithms

      • Dmitry S. Yershov, Steven M. LaValle

      Pages 303-320

   3. Grasp Invariance

      • Alberto Rodriguez, Matthew T. Mason

      Pages 321-336

Robotics is at the cusp of dramatic transformation. Increasingly complex robots with unprecedented autonomy are finding new applications, from medical surgery, to construction, to home services. Against this background, the algorithmic foundations of robotics are becoming more crucial than ever, in order to build robots that are fast, safe, reliable, and adaptive. Algorithms enable robots to perceive, plan, control, and learn. The design and analysis of robot algorithms raise new fundamental questions that span computer science, electrical engineering, mechanical engineering, and mathematics. These algorithms are also finding applications beyond robotics, for example, in modeling molecular motion and creating digital characters for video games and architectural simulation. The Workshop on Algorithmic Foundations of Robotics (WAFR) is a highly selective meeting of leading researchers in the field of robot algorithms. Since its creation in 1994, it has published some of the field’s most important and lasting contributions. This book contains the proceedings of the 9th WAFR, held on December 13-15, 2010 at the National University of Singapore. The 24 papers included in this book span a wide variety of topics from new theoretical insights to novel applications.

• Algorithmic Foundations of Robotics
• Robot Algorithms
• Robotics

• School of Computing, National University of Singapore, Singapore

  David Hsu

• Department of Computer Science, University of Minnesota, Minneapolis, USA

  Volkan Isler

• Computer Science Department, Stanford University, Stanford, USA

  Jean-Claude Latombe

• Department of Computer Science, University of North Carolina, Chapel Hill, Chapel Hill, USA

  Ming C. Lin

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