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, w...
详细信息
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.
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 o...
详细信息
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.
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 ...
详细信息
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)
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 qu...
详细信息
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.
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 algorithm...
详细信息
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.
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 ar...
详细信息
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.
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 expon...
详细信息
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 p...
详细信息
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.
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 typical...
详细信息
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.
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...
详细信息
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.
暂无评论