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Reachability-Based Delayed Decision Guidance for Conventional Interceptors 63

63rd Israel Annual Conference on Aerospace Sciences, IACAS 2024

作者： Shalumov, Vitaly Merkulov, Gleb Shima, Tal Technion – Israel Institute of Technology Haifa3200003 Israel The Technion Program for Autonomous Systems and Robotics Israel Faculty of Aerospace Engineering Israel

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Robust Sliding Mode Based Finite-time Bilateral Shared Teleoperation System with Unsymmetrical Time-Varying Delay* 48

Robust Sliding Mode Based Finite-time Bilateral Shared Teleo...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Islam, Shafiqul Sunda-Meya, Anderson Xavier University of Louisiana Dual Degree Engineering Program Intelligent Robotics Mechatronics & Autonomous Systems Lab New Orleans70125 United States Xavier University of Louisiana College of Arts & Sciences New Orleans70125 United States

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

This paper presents sliding mode-based finite-time synchronization algorithms for bilateral shared teleoperation systems under unsymmetrical time-varying delay and uncertainty. The synchronization algorithms are designed by using Lyapunov and sliding mode control theory. First, the model-based finite-time synchronization algorithms are designed by using sliding mode control theory with the presence of time-varying delays and uncertainty. Then, robust adaptive finite-time synchronization algorithms are designed for bilateral shared teleoperation systems with the presence of time-varying delays. Adaptive learning algorithms learn and adapt with uncertainty associated with the unmodeled dynamics and external disturbances. Lyapunov analysis shows that the tracking errors between master and slave manipulators converge to the sliding surface in finite time. It also shows that the tracking errors asymptotically converge to zero on the sliding surface. The design provides finite-time convergence of the states to reach the sliding surface as opposed to asymptotic convergence-based bilateral shared teleoperation systems. The design and analysis do not use the exact bound of the uncertainty. In contrast with asymptotic design, finite-time convergence can ensure faster and more robust tracking in the presence of uncertainty and time-varying delays. Unlike reported designs, the proposed algorithms can ensure convergence with the presence of unsymmetrical time-varying delays. © 2022 IEEE.

关键词： Time delay

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A Slices Perspective for Incremental Nonparametric Inference in High Dimensional State Spaces

A Slices Perspective for Incremental Nonparametric Inference...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Moshe Shienman Ohad Levy-Or Michael Kaess Vadim Indelman Technion Autonomous Systems Program (TASP) Technion - Israel Institute of Technology Haifa Israel Robotics Institute Carnegie Mellon University Pittsburgh PA USA Department of Aerospace Engineering Technion - Israel Institute of Technology Haifa Israel

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

We introduce an innovative method for incremental nonparametric probabilistic inference in high-dimensional state spaces. Our approach leverages slices from highdimensional surfaces to efficiently approximate posterior distributions of any shape. Unlike many existing graph-based methods, our slices perspective eliminates the need for additional intermediate reconstructions, maintaining a more accurate representation of posterior distributions. Additionally, we propose a novel heuristic to balance between accuracy and efficiency, enabling real-time operation in nonparametric scenarios. In empirical evaluations on synthetic and real-world datasets, our slices approach consistently outperforms other state-of-the-art methods. It demonstrates superior accuracy and achieves a significant reduction in computational complexity, often by an order of magnitude.

关键词： Surface reconstruction Accuracy Shape Probabilistic logic Real-time systems Iterative methods Computational complexity Intelligent robots

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On the Minimal Recognizable Image Patch

On the Minimal Recognizable Image Patch

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International Conference on Pattern Recognition

作者： Mark Fonaryov Michael Lindenbaum Autonomous Systems and Robotics Program Technion Haifa Israel Haifa Israel

In contrast to human vision, common recognition algorithms often fail on partially occluded images. We propose characterizing, empirically, the algorithmic limits by finding a minimal recognizable patch (MRP) that is by itself sufficient to recognize the image. A specialized deep network allows us to find the most informative patches of a given size, and serves as an experimental tool. A human vision study recently characterized related (but different) minimally recognizable configurations (MIRCs) [1], for which we specify computational analogues (denoted cMIRCs). The drop in human decision accuracy associated with size reduction of these MIRCs is substantial and sharp. Interestingly, such sharp reductions were also found for the computational versions we specified.

关键词： Image recognition Tools Character recognition Task analysis Materials requirements planning

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An Evaluation of Direct Image Based Visual Tracking System for autonomous Manipulation* 48

An Evaluation of Direct Image Based Visual Tracking System f...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Islam, S. Saleh, A. Dias, J. Sunda-Meya, A. Xavier University of Louisiana Dual Degree Engineering Program Intelligent Robotics Mechatronics & Autonomous Systems Lab 1 Drexel Drive New OrleansLA70125 United States Khalifa University United Arab Emirates Coimbra3030-260 Portugal Khalifa University Khalifa University Autonomous Vehicles Lab United Arab Emirates Xavier University of Louisiana College of Arts & Sciences 1 Drexel Drive New OrleansLA70125 United States

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

In this paper, we implement and evaluate a direct image-based visual tracking system for autonomous manipulation applications. The direct image-based visual tracking method is developed to relax complex image processing tasks from traditional image and position-based visual tracking methods. The visual signals are constructed by using multiresolution coefficients. The method compares the multiresolution image transformation of the current and desired images and uses the mismatch between them to drive the system. The method needs to design a multiresolution interaction matrix with half and details images. The matrix connects the multiresolution image transformation coefficients with the velocity of the manipulator and controller. To illustrate the effectiveness, the direct image-based tracking system design is implemented and evaluated to locate the position of the valve stem and set of wrenches for autonomous grasping and manipulation for fire fighting applications. © 2022 IEEE.

关键词： Linear transformations

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Is a Simulation better than Teleoperation for Acquiring Human Manipulation Skill Data?

Is a Simulation better than Teleoperation for Acquiring Huma...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Donghyeon Kim Seong-Su Park Kwang-Hyun Lee Dongheui Lee Jee-Hwan Ryu Robotics Program Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Civil and Environmental Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Applied Science Research Institute Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Autonomous Systems Technische Universitat Wien (TU Wien) Vienna Austria

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This study explores the feasibility of using simulations as a better interface to collect human object manipulation skills for learning from demonstrations (LfD). Recently, numerous researchers have started introducing teleoperation systems to acquire human manipulation skills. However, capturing the subtle, force-involved interaction skills of humans in teleoperation is still challenging due to its inherent dynamic delays and feedback transparency. This research evaluates the effectiveness of demonstration data obtained through simulation versus teleoperation. To evaluate the efficacy of this approach, tasks such as plane cutting, tight peg-in-hole, and deformable pipe plugging were performed to assess the quality of demonstrations acquired. The experimental results highlight the effectiveness of demonstration through simulation in capturing the operator’s force-involved interaction skills. Simulation creates an environment similar to performing tasks with bare hands by minimising dynamic delays due to the exclusion of physical robots and effectively rendering high stiffness. As a result, the demonstration through simulation method has proven effective in extracting interaction data and capturing physical task performance skills.

关键词： Hands Dynamics Rendering (computer graphics) Data models Delays Data mining Intelligent robots

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Efficient belief space planning in high-dimensional state spaces using PIVOT: Predictive incremental variable ordering tactic

arXiv

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arXiv 2021年

作者： Elimelech, Khen Indelman, Vadim Robotics and Autonomous Systems Program Technion-Israel Institute of Technology Haifa3200003 Israel Department of Aerospace Engineering Technion-Israel Institute of Technology

In this work, we examine the problem of online decision making under uncertainty, which we formulate as planning in the belief space. Maintaining beliefs (i.e., distributions) over high-dimensional states (e.g., entire trajectories) was not only shown to significantly improve accuracy, but also allows planning with information-theoretic objectives, as required for the tasks of active SLAM and information gathering. Nonetheless, planning under this "smoothing" paradigm holds a high computational complexity, which makes it challenging for online solution. Thus, we suggest the following idea: before planning, perform a standalone state variable reordering procedure on the initial belief, and "push forwards" all the predicted loop closing variables. Since the initial variable order determines which subset of them would be affected by incoming updates, such reordering allows us to minimize the total number of affected variables, and reduce the computational complexity of candidate evaluation during planning. We call this approach PIVOT: Predictive Incremental Variable Ordering Tactic. Applying this tactic can also improve the state inference efficiency;if we maintain the PIVOT order after the planning session, then we should similarly reduce the cost of loop closures, when they actually occur. To demonstrate its effectiveness, we applied PIVOT in a realistic active SLAM simulation, where we managed to significantly reduce the computation time of both the planning and inference sessions. The approach is applicable to general distributions, and induces no loss in accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Computational complexity

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Fluid-driven traveling waves in soft robots

arXiv

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arXiv 2021年

作者： Salem, Lior Gat, Amir D. Or, Yizhar Faculty of Mechanical Engineering TASP- Technion Autonomous Systems and Robotics Program Technion - Israel Institute of Technology Technion City Haifa3200003 Israel

Many marine creatures, gastropods, and earthworms generate continuous traveling waves in their bodies for locomotion within marine environments, complex surfaces, and inside narrow gaps. In this work, we study theoretically and experimentally the use of embedded pneumatic networks as a mechanism to mimic nature and generate bi-directional traveling waves in soft robots. We apply long-wave approximation to theoretically calculate the required distribution of pneumatic network and inlet pressure oscillations needed to create desired moving wave patterns. We then fabricate soft robots with internal pneumatic network geometry based on these analytical results. The experimental results agree well with our model and demonstrate the propagation of moving waves in soft robots, along with locomotion capabilities. The presented results allow fabricating soft robots capable of continuous moving waves via the common approach of embedded pneumatic networks and requiring only two input controls. Copyright © 2021, The Authors. All rights reserved.

关键词： Fluid structure interaction

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Simplified decision making in the belief space using belief sparsification

arXiv

引用

arXiv 2019年

作者： Elimelech, Khen Indelman, Vadim Robotics and Autonomous Systems Program Technion — Israel Institute of Technology Department of Aerospace Engineering Technion — Israel Institute of Technology

In this work, we introduce a new and efficient solution approach for the problem of decision making under uncertainty, which can be formulated as decision making in a belief space, over a possibly high-dimensional state space. Typically, to solve a decision problem, one should identify the optimal action from a set of candidates, according to some objective. We claim that one can often generate and solve an analogous yet simplified decision problem, which can be solved more efficiently. A wise simplification method can lead to the same action selection, or one for which the maximal loss in optimality can be guaranteed. Furthermore, such simplification is separated from the state inference and does not compromise its accuracy, as the selected action would finally be applied on the original state. First, we present the concept for general decision problems and provide a theoretical framework for a coherent formulation of the approach. We then practically apply these ideas to decision problems in the belief space, which can be simplified by considering a sparse approximation of their initial belief. The scalable belief sparsification algorithm we provide is able to yield solutions which are guaranteed to be consistent with the original problem. We demonstrate the benefits of the approach in the solution of a realistic active-SLAM problem and manage to significantly reduce computation time, with no loss in the quality of solution. This work is both fundamental and practical, and holds numerous possible extensions. Copyright © 2019, The Authors. All rights reserved.

关键词： Decision making

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Parameter Optimization and Learning in a Spiking Neural Network for UAV Obstacle Avoidance targeting Neuromorphic Processors

arXiv

引用

arXiv 2019年

作者： Salt, Llewyn Howard, David Indiveri, Giacomo Sandamirskaya, Yulia School of Information Technology and Electrical Engineering University of Queensland QLD Australia Robotics and Autonomous Systems Group in the Cyberphysical System Program CSIRO QLD Australia Institute of Neuroinformatics University of Zurich ETH Zurich Zurich Switzerland

he Lobula Giant Movement Detector (LGMD) is an identified neuron of the locust that detects looming objects and triggers the insect’s escape responses. Understanding the neural principles and network structure that lead to these fast and robust responses can facilitate the design of efficient obstacle avoidance strategies for robotic applications. Here we present a neuromorphic spiking neural network model of the LGMD driven by the output of a neuromorphic Dynamic Vision Sensor (DVS), which incorporates spiking frequency adaptation and synaptic plasticity mechanisms, and which can be mapped onto existing neuromorphic processor chips. However, as the model has a wide range of parameters, and the mixed signal analogue-digital circuits used to implement the model are affected by variability and noise, it is necessary to optimise the parameters to produce robust and reliable responses. Here we propose to use Differential Evolution (DE) and Bayesian Optimisation (BO) techniques to optimise the parameter space and investigate the use of Self-Adaptive Differential Evolution (SADE) to ameliorate the difficulties of finding appropriate input parameters for the DE technique. We quantify the performance of the methods proposed with a comprehensive comparison of different optimisers applied to the model, and demonstrate the validity of the approach proposed using recordings made from a DVS sensor mounted on a UAV. Copyright © 2019, The Authors. All rights reserved.

关键词： Neural networks

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