5,950 research outputs found

    Search Methods for Mobile Manipulator Performance Measurement

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    Mobile manipulators are a potential solution to the increasing need for additional flexibility and mobility in industrial robotics applications. However, they tend to lack the accuracy and precision achieved by fixed manipulators, especially in scenarios where both the manipulator and the autonomous vehicle move simultaneously. This thesis analyzes the problem of dynamically evaluating the positioning error of mobile manipulators. In particular, it investigates the use of Bayesian methods to predict the position of the end-effector in the presence of uncertainty propagated from the mobile platform. Simulations and real-world experiments are carried out to test the proposed method against a deterministic approach. These experiments are carried out on two mobile manipulators - a proof-of-concept research platform and an industrial mobile manipulator - using ROS and Gazebo. The precision of the mobile manipulator is evaluated through its ability to intercept retroreflective markers using a photoelectric sensor attached to the end-effector. Compared to the deterministic search approach, we observed improved interception capability with comparable search times, thereby enabling the effective performance measurement of the mobile manipulator

    Exploiting a new level of DLP in multimedia applications

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    This paper proposes and evaluates MOM: a novel ISA paradigm targeted at multimedia applications. By fusing conventional vector ISA approaches together with more recent SIMD-like (Single Instruction Multiple Data) ISAs (such as MMX), we have developed a new matrix oriented ISA which efficiently deals with the small matrix structures typically found in multimedia applications. MOM exploits a level of DLP not reachable by neither conventional vector ISAs nor SIMD-like media ISA extensions. Our results show that MOM provides a factor of 1.3x to 4x performance improvement when compared with two different multimedia extensions (MMX and MDMX) on several kernels, which translates into up to a 50% of performance gain when measuring full applications (20% in average). Furthermore, the streaming nature of MOM provides additional advantages for executing multimedia applications, such as a very low fetch pressure or a high tolerance to memory latency, making MOM an ideal candidate for the embedded domain.Peer ReviewedPostprint (published version

    Runway exit designs for capacity improvement demonstrations. Phase 2: Computer model development

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    The development is described of a computer simulation/optimization model to: (1) estimate the optimal locations of existing and proposed runway turnoffs; and (2) estimate the geometric design requirements associated with newly developed high speed turnoffs. The model described, named REDIM 2.0, represents a stand alone application to be used by airport planners, designers, and researchers alike to estimate optimal turnoff locations. The main procedures are described in detail which are implemented in the software package and possible applications are illustrated when using 6 major runway scenarios. The main output of the computer program is the estimation of the weighted average runway occupancy time for a user defined aircraft population. Also, the location and geometric characteristics of each turnoff are provided to the user

    Mobile robotic network deployment for intruder detection and tracking

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    This thesis investigates the problem of intruder detection and tracking using mobile robotic networks. In the first part of the thesis, we consider the problem of seeking an electromagnetic source using a team of robots that measure the local intensity of the emitted signal. We propose a planner for a team of robots based on Particle Swarm Optimization (PSO) which is a population based stochastic optimization technique. An equivalence is established between particles generated in the traditional PSO technique, and the mobile agents in the swarm. Since the positions of the robots are updated using the PSO algorithm, modifications are required to implement the PSO algorithm on real robots to incorporate collision avoidance strategies. The modifications necessary to implement PSO on mobile robots, and strategies to adapt to real environments are presented in this thesis. Our results are also validated on an experimental testbed. In the second part, we present a game theoretic framework for visibility-based target tracking in multi-robot teams. A team of observers (pursuers) and a team of targets (evaders) are present in an environment with obstacles. The objective of the team of observers is to track the team of targets for the maximum possible time. While the objective of the team of targets is to escape (break line-of-sight) in the minimum time. We decompose the problem into two layers. At the upper level, each pursuer is allocated to an evader through a minimum cost allocation strategy based on the risk of each evader, thereby, decomposing the agents into multiple single pursuer-single evader pairs. Two decentralized allocation strategies are proposed and implemented in this thesis. At the lower level, each pursuer computes its strategy based on the results of the single pursuer-single evader target-tracking problem. We initially address this problem in an environment containing a semi-infinite obstacle with one corner. The pursuer\u27s optimal tracking strategy is obtained regardless of the evader\u27s strategy using techniques from optimal control theory and differential games. Next, we extend the result to an environment containing multiple polygonal obstacles. We construct a pursuit field to provide a guiding vector for the pursuer which is a weighted sum of several component vectors. The performance of different combinations of component vectors is investigated. Finally, we extend our work to address the case when the obstacles are not polygonal, and the observers have constraints in motion

    Formation Control Algorithms With Limited or No Communication

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    Formation control refers to a collective behaviour of multi-agent systems where individual agents come together to form a pattern, often geometric. These formations can enable multi-agent systems to function more effectively in a broad range of applications. Many formation control algorithms require centralized decision making, communication between agents or a centralized decision maker and other factors that increase per-agent cost and reduce the robustness and scalability of multi-agent systems. To this end, we introduce two algorithms that operate using local decision making and limited or no communication. The first algorithm is a communication-free and index-free algorithm based on polar indicator distributions. The second is a progressive assignment algorithm using limited, situated communication that deterministically assigns agents a position in the objective formation along a convex spiral directed path graph. We also present an extension of the second algorithm for 3-dimensional formation definitions. The first algorithm is demonstrated in a physical experiment using ground-based agents while the second one is simulated using micro air vehicles (MAVs) in a physics-based simulator

    Investigating low-bitrate, low-complexity H.264 region of interest techniques in error-prone environments

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    The H.264/AVC video coding standard leverages advanced compression methods to provide a significant increase in performance over previous CODECs in terms of picture quality, bitrate, and flexibility. The specification itself provides several profiles and levels that allow customization through the use of various advanced features. In addition to these features, several new video coding techniques have been developed since the standard\u27s inception. One such technique known as Region of Interest (RoI) coding has been in existence since before H.264\u27s formalization, and several means of implementing RoI coding in H.264 have been proposed. Region of Interest coding operates under the assumption that one or more regions of a sequence have higher priority than the rest of the video. One goal of RoI coding is to provide a decrease in bitrate without significant loss of perceptual quality, and this is particularly applicable to low complexity environments, if the proper implementation is used. Furthermore, RoI coding may allow for enhanced error resilience in the selected regions if desired, making RoI suitable for both low-bitrate and error-prone scenarios. The goal of this thesis project was to examine H.264 Region of Interest coding as it applies to such scenarios. A modified version of the H.264 JM Reference Software was created in which all non-Baseline profile features were removed. Six low-complexity RoI coding techniques, three targeting rate control and three targeting error resilience, were selected for implementation. Error and distortion modeling tools were created to enhance the quality of experimental data. Results were gathered by varying a range of coding parameters including frame size, target bitrate, and macroblock error rates. Methods were then examined based on their rate-distortion curves, ability to achieve target bitrates accurately, and per-region distortions where applicable
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