17815023
Experimental study on adaptive control of underwater robots
The control of underwater robots presents a number of unique and formidable challenges. Underwater robot dynamics are highly nonlinear, coupled, and time-varying, and subject to hydrodynamic uncertainties and external disturbances such as current. Unlike land mobile robots, underwater robots cannot use GPS. Most popular underwater positioning sensors are sonar-based, such as long-base line. However, autonomous processing of sonar measurements is plagued by noise, drop-outs, missed detection, false reading, poor resolution, etc. The paper presents a new adaptive control of underwater robots with sonar-based position measurements. Experimental results show robustness of the control system in the presence of unmodelled dynamics and various noise.
41633235
Automatic generation of error recovery knowledge through learned reactivity
Develops a new method for automatic generation of error recovery procedures in the assembly workcell. Current reactive systems have integrated planning and learning capabilities to allow them to augment their store of reactive behaviors whenever they are forced to plan. The cycle of evaluation and reaction used by these systems implicitly detects and corrects any errors made in prior behavior execution. By capitalizing on this analogy to error recovery, the authors are able to gain the benefits of a reactive system for use in error recovery while minimizing the perception and evaluation burden that is inherent in those approaches. The authors present a system that uses the new learning reactive paradigm to quickly correct known errors and autonomously learn to recover new errors without human intervention.<<ETX>>
38422944
Neural-Network-Based Fuzzy Logic Control and Decision System
A general neural-network (connectionist) model for fuzzy logic control and decision systems is proposed. This connectionist model, in the form of feedforward multilayer net, combines the idea of fuzzy logic controller and neural-network structure and learning abilities into an integrated neural-network-based fuzzy logic control and decision system. A fuzzy logic control decision network is constructed automatically by learning the training examples itself. By combining both unsupervised (self-organized) and supervised learning schemes, the learning speed converges much faster than the original backpropagation learning algorithm. The connectionist structure avoids the rule-matching time of the inference engine in the traditional fuzzy logic system. Two examples are presented to illustrate the performance and applicability of the proposed model. >
1173830
A genetic-algorithm-based neighbor-selection strategy for hybrid peer-to-peer networks
BitTorrent is a popular, open-source, hybrid peer-to-peer content distribution system that is conducive for distribution of large-volume contents. In this paper, we propose a genetic-algorithm-based neighbor-selection strategy for hybrid peer-to-peer networks, which enhances the decision process performed at the tracker for transfer coordination. We also investigate how the strategy affects system throughput and distribution efficiency as well as peer contributions. We show through computer simulations that by increasing content availability to the clients from their immediate neighbors, it can significantly improve the system performance without trading off users' satisfaction. The proposed strategy can significantly improve the efficiency of distribution, especially for low-connectivity peers, and it is suitable to deploy for online decisions
15498629
Computer Recognition of Two Overlapping Parts Using a Single Camera
The combination of computer vision to recognize overlapping objects and computer-based robots to acquire, orient, and transport these objects will revolutionize manufacturing technology. The bin-picking application, where robots transport randomly scattered parts from a bin and place them on a conveyor with the proper orientation, will significantly improve and economize many manufacturing processes. Equipping the robot with "sight" and the ability to recognize overlapping objects is a first step in solving the bin-picking problem. Recently, many image processing techniques have been applied to the recognition of non-overlapping objects. 1,2 The most successful of these use histogram techniques for segmenting objects from the background and then finding local features such as holes, curves, and corners;3 gradient analysis and Laplacian derivatives for locating edges; 4 and chain-encoding for representing edges and boundaries." Engineers have also employed line-thinning , line-merging, tracking, smoothing , and filtering techniques for image enhancement and sharpening;' and Opinions, findings, and conclusions or recommnenda-dons expressed in this article are those of the authors. maximal cliques,7 template matching, edge-cues, 8 and local feature cues9 for recognizing the object, its position and orientation. (Several techniques are described in the glossary following this article.) A system that determines the position and orientation of non-overlapping objects, and passes that information to a PUMA robot arm for acquisition and transporation, has already been developed at the University of Michigan's Robotics Research Laboratory. The basic method employed by this system is quite similar to the SRI vision module. '0 It compares previously taught parameters (or features) such as the area, perimeter, ratio of perimeter squared divided by area, and a radial template with similar parameters from the image calculated in real time. This system and others like it have been successful in recognizing discrete parts; however, they show severe limitations when attempting to recognize overlapping parts. The major problem lies in segmenting the image II-distinguishing two overlap
33610569
Compression-based broadcast strategies in wireless information systems
Data delivery is through broadcast in wireless information systems due to the asymmetric communication property. However, broadcasting data easily wastes large access time because the large amount of data pages needs to be broadcast. In this paper we propose three compression-based strategies considering access order to reduce access time. Then, the expected access time of three proposed strategies is also derived by using the probability model. Our analytic and experimental results show that the compression-based broadcast strategies can dramatically reduce the access time for mobile users (MU).
2177844
Design, performance analysis, and implementation of a super-scalar video-on-demand system
Despite the availability of video-on-demand (VoD) services in a number of cities around the world, large-scale deployment of VoD services in a metropolitan area is still economically impractical. This study presents a novel super-scalar architecture for building very large-scale and efficient VoD systems. The proposed architecture combines the use of static multicast, dynamic multicast, and intelligent client-side caching to vastly reduce server and network resource requirement. Moreover, in sharp contrast to conventional VoD systems where the system cost increases at least linearly with the system scale, the proposed architecture becomes more efficient as the system scales up and can ultimately be scaled up to serve any number of users while still keeping the startup latency short. This paper presents this new architecture, proposes methods to support interactive playback controls without the need for additional server or client resources, and derives an approximate performance model to relate the startup latency with other system parameters. The performance model is validated using simulation and the architecture is evaluated under various system settings. Lastly, a system implementation is presented and benchmarking results obtained to further verify the architecture, the performance model, and the simulation results.
32212919
Balancing loads on sonet rings with integer demand splitting
SONET Self Healing ring is one of the most intriguing schemes which provide survivability for telecommunication networks. To design a cost effective SONET ring it is necessary to consider load balancing problems by which the link capacity is determined. In this paper, we consider the load balancing problem in SONET ring when demand splitting is allowed only by integer. A bounded approximation to the optimal solution is presented and proved by employing the arc-demand matrix which represents the amount of demand routed on each arc. A very efficient algorithm is provided which always satisfies the optimality at termination. The algorithm iteratively decreases the maximum load by considering counter-clockwise routing of a demand which passes through the arc with maximum load. Justification of the algorithm is also provided.
7325845
Probabilistic QoS guarantee in reliability and timeliness domains in wireless sensor networks
In this paper, we present a novel packet delivery mechanism called multi-path and multi-speed routing protocol (MMSPEED) for probabilistic QoS guarantee in wireless sensor networks. The QoS provisioning is performed in two quality domains, namely, timeliness and reliability. Multiple QoS levels are provided in the timeliness domain by guaranteeing multiple packet delivery speed options. In the reliability domain, various reliability requirements are supported by probabilistic multipath forwarding. All these for QoS provisioning are realized in a localized way without global network information by employing localized geographic packet forwarding augmented with dynamic compensation, which compensates the local decision inaccuracy as a packet travels towards its destination. This way, MMSPEED can guarantee end-to-end requirements in a localized way, which is desirable for scalability and adaptability to large scale dynamic sensor networks. Simulation results show that MMSPEED provides QoS differentiation in both reliability and timeliness domains and, as a result, significantly improves the effective capacity of a sensor network in terms of number of flows that meet both reliability and timeliness requirements.
20686264
Finite-Horizon Scheduling of Radar Dwells with Online Template Construction
Timing constraints for radar tasks are usually specified in terms of the minimum and maximum temporal distance between successive radar dwells. We utilize the idea of feasible intervals for dealing with the temporal distance constraints. In order to increase the freedom that the scheduler can offer a high-level resource manager, we introduce a technique for nesting and interleaving dwells online while accounting for the energy constraint that radar systems need to satisfy. Further, in radar systems, the task set changes frequently and we advocate the use of finite horizon scheduling in order to avoid the pessimism that is inherent in schedulers that assume a task executes forever. We also develop the notion of modular schedule update which allows portions of a schedule to be altered without affecting the entire schedule, thereby simplifying the scheduler. Through extensive simulations, we validate our claims of providing greater scheduling flexibility without compromising on performance when compared with earlier work based on templates constructed offline.