1 RESUME PAUL G. SPIRAKIS (1) Full Professor Dept. of Computer
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Toward Autonomous Robots
Toward Autonomous Rob ots: Robust, Adaptive and Dynamic Motion John Reif Department of Computer Science, Duke University Abstract Wewere engaged in researchinvarious areas of rob otic movement planning. The movement planning problems investigated were static movement problems where the obstacles do not move, minimum distance path planning, compliant motion control whichinvolves planning without complete knowledge of the p osition of the rob ot and related frictional movement problems, motion planning with indep en- dently moving obstacles, and kino dynamic movement planning where the dynamics are taken into account including driving forces and torque, motion planning within p otential elds such as gravitational force p otential elds and magnetic elds and pursuit movement games whichinvolvemovement control planning with an adver- sary. Most of our e orts were involved in the latter problems which have b een investigated less. This pap er will present some of our lates results on these various problems. Also this pap er will include some improved algorithms we develop ed for the fundamental algebraic and combinatorial problems such as ro ot nding which app ear frequently as subproblems in these rob ot movement planning problems. 1 Intro duction Robotics movement planning problem or robotics motion planning problem is to plan an obstacle-free path or tra jectory for a rob ot from a sp eci ed initial con- guration p osition, orientation, etc. to a sp eci ed nal con guration. It is one of the most fundamental problems in rob otics research. No matter what purp ose a rob ot is designed for, the rst task is how to plan the rob ot to move in its working space, while avoiding p ossible obstacles, to reach a desired con guration. -
Games, Puzzles, and Computation Robert Aubrey Hearn
Games, Puzzles, and Computation by Robert Aubrey Hearn B.A., Rice University (1987) S.M., Massachusetts Institute of Technology (2001) Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY June 2006 c Massachusetts Institute of Technology 2006. All rights reserved. Author.............................................................. Department of Electrical Engineering and Computer Science May 23, 2006 Certified by. Erik D. Demaine Esther and Harold E. Edgerton Professor of Electrical Engineering and Computer Science Thesis Supervisor Certified by. Gerald J. Sussman Matsushita Professor of Electrical Engineering Thesis Supervisor Accepted by......................................................... Arthur C. Smith Chairman, Department Committee on Graduate Students Games, Puzzles, and Computation by Robert Aubrey Hearn Submitted to the Department of Electrical Engineering and Computer Science on May 23, 2006, in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science Abstract There is a fundamental connection between the notions of game and of computation. At its most basic level, this is implied by any game complexity result, but the connec- tion is deeper than this. One example is the concept of alternating nondeterminism, which is intimately connected with two-player games. In the first half of this thesis, I develop the idea of game as computation to a greater degree than has been done previously. I present a general family of games, called Constraint Logic, which is both mathematically simple and ideally suited for reductions to many actual board games. A deterministic version of Constraint Logic corresponds to a novel kind of logic circuit which is monotone and reversible. -
Motion Planning Algorithms
Survey: Motion Planning Algorithms by Leslie Glaves [email protected] CSE638 Topics in Computational Geometry Professor Joe Mitchell Stony Brook University, New York 11794 May 2004 Abstract This paper introduces and surveys current progress in path/motion planning al- gorithms with greater attention given to recent work with RRTs (Rapidly-Exploring Random Trees). 1 Introduction The perennial pursuit of artificial intelligence, that of constructing a robot that can learn on it’s own can be distilled to solving a few essential problems. For a mobile robot, a basic problem is how to plan to move, alternately referred to as path planning or motion planning. Although robotic applications are currently one of the most popular and highly publicized topics in motion planning, planning and solving collision free paths is required for many other computational pursuits. Motion planning is used in graphic animation and video game software, navigation within virtual environments, physics-based simulation, CAGD (computer-aided geometric design), molecular dynamics (such as binding and folding), vir- tual prototyping, computer controlled medical surgery and for computerized navigation of all types of vehicles (wheeled, aircraft, spacecraft, etc). Study of motion planning is encom- passed by several disciplines, including (but not limited to): Computer Science, Artificial Intelligence, Robotics, Mechanical Engineering, Computational Geometry and Differential Geometry. 1 The most basic motion planning problem is to compute a collision-free path from start loca- tion to goal location in a static environment containing obstacles which must be manuvered around. In reality, motion planning often involves reaching a goal location while obstacles are moving in the environment and optimized paths are desired. -
Mechcomp2017.Pdf
Mechanical Computation: The Computational Complexity of Physical Computing Devices Chapter, Encyclopedia of Complexity and Systems Science1 John H. Reif2 Article Outline Glossary I. Definition of the Subject and Its Importance II. Introduction to Computational Complexity III. Computational Complexity of Mechanical Devices and their Movement Problems IV. Concrete Mechanical Computing Devices V. Future Directions VI. Bibliography Glossary - Mechanism: A machine or part of a machine that performs a particular task computation: the use of a computer for calculation. - Computable: Capable of being worked out by calculation, especially using a computer. - Simulation: Used to denote both the modeling of a physical system by a computer as well as the modeling of the operation of a computer by a mechanical system; the difference will be clear from the context. 1 This is a revised and updated version of John H. Reif, Mechanical Computing: The Computational Complexity of Physical Devices, invited chapter, Encyclopedia of Complexity and System Science (edited by Andrew Spencer), Springer-Verlag, Heidelberg, Germany, (2013). Published online: http://www.springerreference.com/docs/html/chapterdbid/60497.html 2 Department of Computer Science, Duke University, Box 90129, Durham, NC 27708- 90129 USA. E-mail: [email protected]. This work was supported by NSF grants NSF Grants CCF-1217457, CCF-1320360 and CCF-1617791. I. Definition of the Subject and Its Importance Mechanical devices for computation appear to be largely displaced by the widespread use of microprocessor-based computers that are pervading almost all aspects of our lives. Nevertheless, mechanical devices for computation are of interest for at least three reasons: (a) Historical: The use of mechanical devices for computation is of central importance in the historical study of technologies, with a history dating to thousands of years and with surprising applications even in relatively recent times.