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检索条件"丛书名=Springer Tracts in Advanced Robotics"

共 918 条记录，以下是381-390 订阅

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How Should Microrobots Swim?

引用

13th International Symposium on robotics Research (ISSR)

作者： Abbott, Jake J. Peyer, Kathrin E. Dong, Lixin X. Nelson, Bradley J. Swiss Fed Inst Technol Inst Robot & Intelligent Syst CH-8092 Zurich Switzerland

ISBN: (纸本)9783642147432

Microrobots have the potential to dramatically change many aspects of medicine by navigating bodily fluids to perform targeted diagnosis and therapy. Researchers have proposed numerous microrobotic swimming methods, with the vast majority utilizing magnetic fields to wirelessly power and control the microrobot. In this paper, we theoretically and experimentally compare the two most promising methods of microrobot swimming-using magnetic fields to rotate helical propellers that mimic bacterial flagella, and pulling with magnetic field gradients-considering the practical limitations in the generation of magnetic fields. We find that swimming with a helical propeller generally becomes more desirable as size decreases, and will likely be the best choice for in vivo applications.

关键词： Propellers

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Simultaneous Coverage and Tracking (SCAT) of Moving Targets with Robot Networks

引用

8th International Workshop on the Algorithmic Foundations of robotics

作者： Pimenta, Luciano C. A. Schwager, Mac Lindsey, Quentin Kumar, Vijay Rus, Daniela Mesquita, Renato C. Pereira, Guilherme A. S. Univ Penn Grasp Lab Philadelphia PA 19104 USA MIT CSAIL Cambridge MA 02139 USA Univ Fed Minas Gerais Dept Engn Elet Belo Horizonte MG Brazil

ISBN: (纸本)9783642003110

We address the problem of simultaneously covering an environment and tracking intruders (SCAT). The problem is translated to the task of covering environments with time-varying density functions under the locational optimization framework. This allows for coupling the basic subtasks: task assignment, coverage, and tracking. A decentralized controller with guaranteed exponential convergence is devised. The SCAT algorithm is verified in simulations and on a team of robots.

关键词： Target tracking

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Multiagent Pursuit Evasion, or Playing Kabaddi

引用

9th International Workshop on the Algorithmic Foundations of robotics

作者： Klein, Kyle Suni, Subhash Univ Calif Santa Barbara Santa Barbara CA 93106 USA

ISBN: (纸本)9783642174513

We study a version of pursuit evasion where two or more pursuers are required to capture the evader because the evader is able to overpower a single defender. The pursuers must coordinate their moves to fortify their approach against the evader while the evader maneuvers to disable pursuers from their unprotected sides. We model this situation as a game of Kabaddi, a popular South Asian sport where two teams occupy opposite halves of a field and take turns sending an attacker into the other half, in order to win points by tagging or wrestling members of the opposing team, while holding his breath during the attack. The game involves team coordination and movement strategies, making it non-trivial to formally model and analyze, yet provides an elegant framework for the study of multiagent pursuit-evasion, for instance, a team of robots attempting to capture a rogue agent. Our paper introduces a simple discrete (time and space) model for the game, offers analysis of winning strategies, and explores tradeoffs between maximum movement speed, number of pursuers, and locational constraints.(1)

关键词： Models, Space tradeoffs Breath Robot Wrestling discrete-time

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

引用

9th International Workshop on Algorithmic Foundations of robotics (WAFR)

作者： Nechushtan, Oren Raveh, Barak Halperin, Dan Tel Aviv Univ Sch Comp Sci Tel Aviv Israel

ISBN: (纸本)9783642174513

Sampling-based motion planners are a central tool for solving motion-planning problems in a variety of domains, but the theoretical understanding of their behavior remains limited, in particular with respect to the quality of the paths they generate (in terms of path length, clearance, etc.). In this paper we prove, for a simple family of obstacle settings, that the popular dual-tree planner Bi-RRT may produce low-quality paths that are arbitrarily worse than optimal with modest but significant probability, and overlook higher-quality paths even when such paths are easy to produce. At the core of our analysis are probabilistic automata designed to reach an accepting state when a path of significantly low quality has been generated. Complementary experiments suggest that our theoretical bounds are conservative and could be further improved. To the best of our knowledge, this is the first work to study the attainability of high-quality paths that occupy a significant (non-negligible) portion of the space of all paths. The formalism presented in this work can be generalized to other algorithms and other motion-planning problems by defining appropriate predicates, and pave the way to deeper understanding of hallmark planning algorithms.

关键词： Motion planning

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Visual Object Tracking Using Positive and Negative Examples

引用

13th International Symposium on robotics Research (ISSR)

作者： Wada, Toshikazu Wakayama Univ Fac Syst Engn Wakayama 6408510 Japan

ISBN: (纸本)9783642147432

This paper presents a robust and real-time object tracking method in image sequences. Existing visual object detection and tracking algorithms usually use apparent features of target object as a model. Those algorithms detects objects by thresholding the similarity or the dissimilarity measure with the model. They sometimes fail to detect objects because of inadequate threshold. In this paper, we propose a method for detection and tracking using positive (object) and negative (non-object) models. This method does not require any threshold, because the object region can be detected just by comparing the similarities or dissimilarities with positive and negative models. If we employ distance as a dissimilarity measure, the problem can be formalized as a nearest neighbor (NN) classification problem. We first show an example of NN classification based color object detection, which detects multiple objects in real-time. Next, we extend the method to tracking. For this extension, we have to measure the distinctiveness of the object, because the detected object by the NN classification sometimes disappears. By finding the high distinctiveness image region around the tracked region in the previous image frame, we can keep tracking even if the object cannot be detected by NN classification. We implemented this method on an active stereo camera system and confirmed that video-rate detection and tracking as well as 3D position measurement can he realized just by using standard PC.

关键词： Object detection

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Two Finger Caging: Squeezing and Stretching

引用

8th International Workshop on the Algorithmic Foundations of robotics

作者： Rodriguez, Alberto Mason, Matthew T. Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA

ISBN: (纸本)9783642003110

This paper studies the problem of placing two point fingers to cage a mobile rigid body in a Euclidean space of arbitrary dimension. (To cage an object is to arrange obstacles so that all motions of the mobile body are bounded). This paper shows that if a compact connected contractible object is caged by two points, then it is either stretching caged or squeezing caged or both, where stretching caged means the body is trapped even if the point fingers are given the freedom of moving apart, and squeezing caged means the the body is trapped even if the fingers are given the freedom of moving closer. This result generalizes a previous result by Vahedi and van der Stappen [18] which applied to two points trapping a polygon in the plane. Our use of a topological approach led to the generalization, and may lead to further generalizations and insights.

关键词： Artificial intelligence

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A Sampling Hyperbelief Optimization Technique for Stochastic Systems

引用

8th International Workshop on the Algorithmic Foundations of robotics

作者： Davidson, James C. Hutchinson, Seth A. Univ Illinois Beckman Inst Chicago IL 60680 USA

ISBN: (纸本)9783642003110

Uncertainty plays a dramatic role not only on the quality of the optimal solution of POMDP system, but also on the computational complexity of finding the optimal solution, with a worst case running time that is exponential in the length of the time horizon for the exact solution. However, given the importance of finding optimal or nearly optimal solutions for systems subject to uncertainty, numerous researchers have developed approaches to approximate POMDP systems to overcome this limitation (refer to [22, Ch. 15 & 16] for a survey of such approaches). The majority of these methods are for discounted, infinite-horizon problems. Moreover, many of these techniques must reperform all the computational effort when the objective function changes. A central theme of almost all approximation techniques is to reduce the set of possibilities to be evaluated, whether simplifying the representation of the belief or by the simplifying the value function. Drawing on insights offered in [8] about why belief sampling techniques (such as [21, 15, 17, 18, 19, 20]) are so effective, we develop an alternative method that is inspired by graph sampling-based methods (e.g., [10]). In [6], we introduce the notion of hyperfiltering, which evolves forward into future stages the probability function over the belief, or the *** refer to the space of probability functions over the belief as the hyperbelief space. Interestingly, the evolution of a system over the hyperbelief space is deterministic. Thus, we can find the optimal plan in the hyperbelief space using an approach derived from standard search techniques. © 2009 springer-Verlag.

关键词： Stochastic systems

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Learning Hierarchical Representations of Object Categories for Robot Vision

引用

13th International Symposium on robotics Research (ISSR)

作者： Leonardis, Ales Fidler, Sanja Univ Ljubljana Fac Comp & Informat Sci Ljubljana 61000 Slovenia

ISBN: (纸本)9783642147432

This paper presents our recently developed approach to constructing a hierarchical representation of visual input that aims to enable recognition and detection of a large number of object categories. Inspired by the principles of efficient indexing, robust matching, and ideas of compositionality, our approach learns a hierarchy of spatially flexible compositions, i.e. parts, in an unsupervised, statistics-driven manner. Starting with simple, frequent features, we learn the statistically most significant compositions (parts composed of parts), which consequently define the next layer. Parts are learned sequentially, layer after layer, optimally adjusting to the visual data. Lower layers are learned in a category-independent way to obtain complex, yet sharable visual building blocks, which is a crucial step towards a scalable representation. Higher layers of the hierarchy, on the other hand, are constructed by using specific categories, achieving a category representation with a small number of highly generalizable parts that gained their structural flexibility through composition within the hierarchy. Built in this way, new categories can be efficiently and continuously added to the system by adding a small number of parts only in the higher layers. The approach is demonstrated on a large collection of images and a variety of abject categories.

关键词： Robot vision

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Bounded Uncertainty Roadmaps for Path Planning

引用

8th International Workshop on the Algorithmic Foundations of robotics

作者： Guibas, Leonidas J. Hsu, David Kurniawati, Hanna Rehman, Ehsan Stanford Univ Stanford CA 94305 USA Natl Univ Singapore Singapore 117417 Singapore

ISBN: (纸本)9783642003110

Motion planning under uncertainty is an important problem in robotics. Although probabilistic sampling is highly successful for motion planning of robots with many degrees of freedom, sampling-based algorithms typically ignore uncertainty during planning. We introduce the notion of a bounded uncertainty roadmap (BURM) and use it to extend sampling-based algorithms for planning under uncertainty in environment maps. The key idea of our approach is to evaluate uncertainty, represented by collision probability bounds, at multiple resolutions in different regions of the configuration space, depending on their relevance for finding a best path. Preliminary experimental results show that our approach is highly effective: our BURM algorithm is at least 40 times faster than an algorithm that tries to evaluate collision probabilities exactly, and it is not much slower than classic probabilistic roadmap planning algorithms, which ignore uncertainty in environment maps.

关键词： Motion planning

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On the Existence of Nash Equilibrium for a Two-player Pursuit-Evasion Game with Visibility Constraints

引用

8th International Workshop on the Algorithmic Foundations of robotics

作者： Bhattacharya, Sourabh Hutchinson, Seth Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA

ISBN: (纸本)9783642003110

In this paper, we present a game-theoretic analysis of a visibility-based pursuit-evasion game in a planar environment containing obstacles. The pursuer and the evader are holonomic having bounded speeds. Both players have a complete map of the environment. Both players have omnidirectional vision and have knowledge about each other's current position as long as they are visible to each other. The pursuer wants to maintain visibility of the evader for the maximum possible time and the evader wants to escape the pursuer's sight as soon as possible. Under this information structure, we present necessary and sufficient conditions for surveillance and escape. We present strategies for the players that are in Nash equilibrium. The strategies are a function of the value of the game. Using these strategies, we construct a value function by integrating the adjoint equations backward in time from the termination situations provided by the corners in the environment. From these value functions we recompute the control strategies for the players to obtain optimal trajectories for the players near the termination situation. This is the first work that presents the necessary and sufficient conditions for tracking for a visibility based pursuit-evasion game and presents the equilibrium strategies for the players.

关键词： game theory pursuit-evasion

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