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
13570447
Paradigm shift and the integrated feedback approach
With the increased competition in today's world market, emphasis has been on the ability to shift from an existing paradigm to a new paradigm so as to create new opportunities and to gain new market. A successful paradigm shift is dependent on two factors: (1) the ability to pinpoint the inherent weaknesses in the existing paradigm, (2) the ability to find a paradigm that can replace the old paradigm. In this paper, we show how the integrated feedback approach is able to address these two concerns. The integrated feedback approach was proposed to integrate the design phase with the downstream activities so as to achieve a design that is better for assembly. The approach operates in two phases: an evaluation phase and a redesign suggestion generation phase. A number of objective criteria have been proposed to evaluate a given design from the functional perspective, from the assembly plan perspective, and from the tolerance perspective. Through the evaluation process, weaknesses in the design are identified and techniques for generating feasible redesign suggestions are examined. By encouraging greater participation from the designer, a systematic aid to paradigm shifting can be obtained. A prototype system implementing the integrated feedback approach has been developed on a Sun Sparcstation with graphics simulation on a Silicon Graphics Iris workstation. A real life product, the telephone, is used as an illustration.
30064492
Genetic reinforcement learning approach to the machine scheduling problem
This paper focuses on the development of a learning-based heuristic for the machine scheduling problem, which automatically captures the search control knowledge or the common features of good schedules while generating a number of schedules. Defining states and actions of the machine shop, the machine scheduling problem is transformed into a problem of reinforcement learning (RL) in which a learner or a scheduler will learn to select the right action at each state of the machine shop, using the reward from a schedule evaluator for executing the action. Implementing the proposed reinforcement learning with a genetic algorithm results in the genetic reinforcement learning (GRL) approach to the machine scheduling problem. Although the learning-based heuristic has the overhead of acquiring knowledge on the problem, it can be easily adapted for a wide variety of machine scheduling problems due to the weak dependence on the problem structures and objectives. A GRL-based scheduler, called EVIS (Evolutionary Intracell Scheduler), has been developed and applied to various classes of machine scheduling problems, such as the job-shop scheduling, the flow-shop scheduling and the open-shop scheduling problems, and even the processor scheduling problem, the performance evaluation of EVIS with a number of different problem instances has shown that the learning-based heuristic is robust and its performance is comparable with that of other problem-specific heuristics or search-oriented heuristics in the quality of solutions.
12503943
Model-based visual feedback control for a hand-eye coordinated robotic system
The integration of a single camera into a robotic system to control the relative position and orientation between the robot's end-effector and a moving part in real time is discussed. Only monocular vision techniques are considered because of current limitations in the speed of computer vision analysis. The approach uses geometric models of both the part and the camera, as well as the extracted image features, to generate the appropriate robot control signals for tracking. Part and camera models are also used during the teaching stage to predict important image features that appear during task completion.<<ETX>>
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
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>>
29820357
Service specific call admission control in WCDMA system
When a new call arrives, the system has to determine whether to accept the call or not. These admission decisions are performed by call admission control (CAC). CAC belongs to the resource management category and is widely being investigated in many other researches as well. However, researches on CAC have mostly focused on channel allocation in the traditional FDMA and TDMA systems. We focus on a WCDMA system, which has no fixed channel capacity. In this study, a new CAC scheme for WCDMA systems is proposed. It also addresses CDMA capacity evaluation and code assignment problems. The proposed scheme consists of handoff and new CACs. For each service class, handoff and new CACs are considered with different priorities. The handoff CAC process precedes that of the new CAC process. Finally, we evaluate the performance of the proposed scheme by using Markov analysis. The performance measures that we focus on are the blocking probabilities of handoff and new calls and the dropping probabilities of on-going calls.
9335901
Performance upgrade for large object bases using disk arrays
The authors propose the use of multiple disks to increase the bandwidth of disk I/O so as to alleviate the I/O bottleneck problem existed in OODB applications. However, a major difficulty in using multiple disks for the support of OODBs is that an object may reference or be referenced by other objects through associations. This requires that the search of objects be sequential through the association links, which is sometimes referred to as the navigational search of objects in an object base. This restriction limits the concurrency in object retrieval and invalidates the use of multiple disks. Techniques such as clustering/indexing of objects do not help to resolve this problem. By using a two-phase query processing strategy previously proposed by them, objects of interest can be accessed in parallel from multiple disk. The aim of the paper is to design a probability-based evaluation model to estimate the performance of using multiple disks and to compare it with a single disk system. The result shows that the scheme is viable and a significant improvement is achieved while multiple disks are used.
41223157
Best Movement of Mobile Agent in Mobile Computing Systems
Retrieving data using mobile agents gains popularity due to the advance of mobile computing techniques. However, the transmission of wireless communication is still unreliable and bandwidth-limited. This paper investigates this issue and tries to find the most suitable location for a mobile agent in a vast network. We first propose a mechanism and operations for the support of this strategy. We then develop an analysis model to estimate the optimal location for a mobile agent.
16111193
Bounding Cache-Related Preemption Delay for Real-Time Systems
Cache memory is used in almost all computer systems today to bridge the ever increasing speed gap between the processor and main memory. However, its use in multitasking computer systems introduces additional preemption delay due to the reloading of memory blocks that are replaced during preemption. This cache-related preemption delay poses a serious problem in realtime computing systems where predictability is of utmost importance. We propose an enhanced technique for analyzing and thus bounding the cache-related preemption delay in fixed-priority preemptive scheduling focusing on instruction caching. The proposed technique improves upon previous techniques in two important ways. First, the technique takes into account the relationship between a preempted task and the set of tasks that execute during the preemption when calculating the cache-related preemption delay. Second, the technique considers the phasing of tasks to eliminate many infeasible task interactions. These two features are expressed as constraints of a linear programming problem whose solution gives a guaranteed upper bound on the cache-related preemption delay. This paper also compares the proposed technique with previous techniques using randomly generated task sets. The results show that the improvement on the worst-case response time prediction by the proposed technique over previous techniques ranges between 5 percent and 18 percent depending on the cache refill time when the task set utilization is 0.6. The results also show that as the cache refill time increases, the improvement increases, which indicates that accurate prediction of cache-related preemption delay by the proposed technique becomes increasingly important if the current trend of widening speed gap between the processor and main memory continues.
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).