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检索条件"任意字段=International Symposium on Computational Intelligence in Robotics and Automation"

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Safe and Efficient Model-free Adaptive Control via Bayesian Optimization

Safe and Efficient Model-free Adaptive Control via Bayesian ...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Konig, Christopher Turchetta, Matteo Lygeros, John Rupenyan, Alisa Krause, Andreas Inspire AG Zurich Switzerland Swiss Fed Inst Technol Learning & Adapt Syst Grp Zurich Switzerland Swiss Fed Inst Technol Automat Control Lab Zurich Switzerland

ISBN: (纸本)9781728190778

Adaptive control approaches yield high-performance controllers when a precise system model or suitable parametrizations of the controller are available. Existing data-driven approaches for adaptive control mostly augment standard model-based methods with additional information about uncertainties in the dynamics or about disturbances. In this work, we propose a purely data-driven, model-free approach for adaptive control. Tuning low-level controllers based solely on system data raises concerns on the underlying algorithm safety and computational performance. Thus, our approach builds on GoOSE, an algorithm for safe and sample-efficient Bayesian optimization. We introduce several computational and algorithmic modifications in GoOSE that enable its practical use on a rotational motion system. We numerically demonstrate for several types of disturbances that our approach is sample efficient, outperforms constrained Bayesian optimization in terms of safety, and achieves the performance optima computed by grid evaluation. We further demonstrate the proposed adaptive control approach experimentally on a rotational motion system.

关键词： Adaptation models Uncertainty computational modeling Heuristic algorithms Bayes methods Safety Adaptive control

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Air force space automation & robotics: An artificial intelligence assesment

Air force space automation & robotics: An artificial intelli...

引用

AIAA/NASA 1st international symposium on Space automation and robotics, 1988

作者： Ferguson, Thomas R. Gersh, Mark A. USAF DCS Technology & Requirements Planning HQ Air Force Systems Command Andrews AFB MD20334 United States AIAA Software Systems Technical Committee Artificial Intelligence Technology Development HQ Air Force Systems Command Andrews AFB MD20334 United States

"Space, the final frontier, to boldly go where no mail has gone before." A though trite, this statement aptly describes the necessity for space automation and robotics. Space is a relatively unfamiliar, inaccessible, and dangerous domain and successful operations there demand a high degree of autonomy. Autonomy enhances operational effectiveness and efficiency by significantly reducing the need for human interaction. It extends mission capability by permitting operations in harsh, austere conditions unsuitable for human involvement. Finally, it can improve mission performance by providing quick solutions to the many problems constantly occurring in such a dynamic environment. While this paper describes today's Air Force presence and highlights tomorrow's planned activities in space, it primarily focuses on those applications where automation & robotics technology is required and on the technology challenges associated with accomplishing such goals. Additionally, the paper discusses the long-standing relationship between the Air Force and NASA and its extension to space operations automation & robotics. This relationship appears to be on the verge of becoming another excellent example of joint cooperation. Finally, the paper concludes by looking to the future and pointing the way to new directions and accomplishments. It assesses the necessary spirit of cooperation which must exist before the space community can expect to fully capitalize and exploit automation & robotics technology to achieve its goals. © 1988 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： NASA

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How morphology affects self-assembly in a stochastic modular robot

How morphology affects self-assembly in a stochastic modular...

引用

IEEE international Conference on robotics and automation

作者： Miyashita, Shuhei Kessler, Marco Lungarella, Max Univ Zurich Dept Informat Artificial Intelligence Lab CH-8006 Zurich Switzerland

ISBN: (纸本)9781424416462

Self-assembly is a process through which an organized structure can spontaneously form from simple parts. Taking inspiration from biological examples of self-assembly, we designed and built a water-based modular robotic system consisting of autonomous plastic tiles capable of aggregation on the surface of water. In this paper, we investigate the effect of the morphology (here: shape) of the tiles on the yield of the self-assembly process, that is, on the final amount of the desired aggregate. We describe experiments done with the real system as well as with a computer simulation thereof. We also present results of a mathematical analysis of the modular system based on chemical rate equations which point to a power-law relationship between yield rate and shape. Using the real system, we further demonstrate how through a single parameter (here: the externally applied electric potential) it is possible to control the self-assembly of propeller-like aggregates. Our results seem to provide a starting point (a) for quantifying the effect of morphology on the yield rates of self-assembly processes and (b) for assessing the level of modular autonomy and computational resources required for emergent functionality to arise.

关键词： Aggregates

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Joint Communication and Motion Planning for Cobots 39

Joint Communication and Motion Planning for Cobots

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Dadvar, Mehdi Majd, Keyvan Oikonomou, Elena Fainekos, Georgios Srivastava, Siddharth Arizona State Univ Sch Comp & Augmented Intelligence Tempe AZ 85287 USA

ISBN: (纸本)9781728196817

The increasing deployment of robots in co-working scenarios with humans has revealed complex safety and efficiency challenges in the computation of the robot behavior. Movement among humans is one of the most fundamental -and yet critical-problems in this frontier. While several approaches have addressed this problem from a purely navigational point of view, the absence of a unified paradigm for communicating with humans limits their ability to prevent deadlocks and compute feasible solutions. This paper presents a joint communication and motion planning framework that selects from an arbitrary input set of robot's communication signals while computing robot motion plans. It models a human co-worker's imperfect perception of these communications using a noisy sensor model and facilitates the specification of a variety of social/workplace compliance priorities with a flexible cost function. Theoretical results and simulator-based empirical evaluations show that our approach efficiently computes motion plans and communication strategies that reduce conflicts between agents and resolve potential deadlocks.

关键词： Robot motion Costs computational modeling Simulation System recovery Robot sensing systems Planning

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Learning an Efficient Terrain Representation for Haptic Localization of a Legged Robot

Learning an Efficient Terrain Representation for Haptic Loca...

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IEEE international Conference on robotics and automation (ICRA)

作者： Sojka, Damian Nowicki, Michal R. Skrzypczynski, Piotr Poznan Univ Tech Inst Robot & Machine Intelligence Poznan Poland

ISBN: (纸本)9798350323658

Although haptic sensing has recently been used for legged robot localization in extreme environments where a camera or LiDAR might fail, the problem of efficiently representing the haptic signatures in a learned prior map is still open. This paper introduces an approach to terrain representation for haptic localization inspired by recent trends in machine learning. It combines this approach with the proven Monte Carlo algorithm to obtain an accurate, computation-efficient, and practical method for localizing legged robots under adversarial environmental conditions. We apply the triplet loss concept to learn highly descriptive embeddings in a transformer-based neural network. As the training haptic data are not labeled, the positive and negative examples are discriminated by their geometric locations discovered while training. We demonstrate experimentally that the proposed approach outperforms by a large margin the previous solutions to haptic localization of legged robots concerning the accuracy, inference time, and the amount of data stored in the map. As far as we know, this is the first approach that completely removes the need to use a dense terrain map for accurate haptic localization, thus paving the way to practical applications.

关键词： computational efficiency

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SOME LOCATION PROBLEM FOR SINGLE-EYE ROBOT NAVIGATION.

SOME LOCATION PROBLEM FOR SINGLE-EYE ROBOT NAVIGATION.

引用

Proceedings - international Workshop on Industrial Applications of Machine Vision and Machine intelligence, Seiken symposium

作者： Sugihara, Kokichi

A class of point location problems found in visual navigation of a mobile robot is considered. The problem is to locate the robot using a map of the room in which it moves and an image taken by a camera that it carries. Vertical edges are extracted from the image, and a possible location for the robot is searched for by establishing a correspondence between the edges in the images and vertical poles given in the map. This problem and some of its variations are considered from the computational geometry point of view, and efficient algorithms for solving them are given.

关键词： robotics

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Active exploration and keypoint clustering for object recognition

Active exploration and keypoint clustering for object recogn...

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IEEE international Conference on robotics and automation

作者： Kootstra, Gert Ypma, Jelmer de Boer, Bart Univ Groningen Artificial Intelligence Inst NL-9712 TS Groningen Netherlands

ISBN: (纸本)9781424416462

Object recognition is a challenging problem for artificial systems. This is especially true for objects that are placed in cluttered and uncontrolled environments. To challenge this problem, we discuss an active approach to object recognition. Instead of passively observing objects, we use a robot to actively explore the objects. This enables the system to learn objects from different viewpoints and to actively select viewpoints for optimal recognition. Active vision furthermore simplifies the segmentation of the object from its background. As the basis for object recognition we use the Scale Invariant Feature Transform (SIFT). SIFT has been a successful method for image representation. However, a known drawback of SIFT is that the computational complexity of the algorithm increases with the number of keypoints. We discuss a growing-when-required (GWR) network for efficient clustering of the keypoints. The results show successful learning of 3D objects in real-world environments. The active approach is successful in separating the object from its cluttered background, and the active selection of viewpoint further increases the performance. Moreover, the GWR-network strongly reduces the number of keypoints.

关键词： Object recognition

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Toward computationally Efficient Path Generation and Push Planning for Robotic Nonprehensile Manipulation 9

Toward Computationally Efficient Path Generation and Push Pl...

引用

9th international Conference on automation, robotics and Applications (ICARA)

作者： Elibol, Armagan Chong, Nak Young Japan Adv Inst Sci & Technol Sch Informat Sci Nomi Ishikawa Japan

ISBN: (纸本)9781665489218

Robots have been involved in our daily life more and more. This involvement comes along with a necessity for endowing robots to interact with real-world objects that are novel to them. Among many others, pushing is one of the important tasks for robotic arms (or manipulators) as it has been widely used in the pipeline of the more complicated tasks (e.g., grasping, singulation, reorienting, and similar other tasks.). In this paper, we present simple yet efficient path generation and push planning algorithms for pushing an object from a given point to a target point in the given grid map with static obstacles. Our path generation module aims to generate waypoints taking into account obstacles and quantizing them into circular regions in order to reduce the computational cost. The path is formed using the waypoints by minimizing the designed cost function. We also define a cost function for planning pushing steps aiming to both minimize the number of pushing actions and deviation from the path generated. We present comparative numerical results using simulated data. Our preliminary findings show promising results leaving room for further improvements.

关键词： robotic arm planar pushing path generation push planning

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Task-Space Decomposed Motion Planning Framework for Multi-Robot Loco-Manipulation

Task-Space Decomposed Motion Planning Framework for Multi-Ro...

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IEEE international Conference on robotics and automation (ICRA)

作者： Zhang, Xiaoyu Yan, Lei Lam, Tin Lun Vijayakumar, Sethu Shenzhen Inst Artificial Intelligence & Robot Soc Shenzhen Peoples R China Univ Edinburgh Sch Informat Edinburgh Midlothian Scotland Chinese Univ Hong Kong Shenzhen Peoples R China Airs Shenzhen Peoples R China

ISBN: (纸本)9781728190778

This paper introduces a novel task-space decomposed motion planning framework km multi-robot simultaneous locomotion and manipulation. When several manipulators hold an object, closed-chain kinematic constraints are formed, and it will make the motion planning problems challenging by inducing lower-dimensional singularities. Unfortunately, the constrained manifold will he even more complicated when the manipulators are equipped with mobile bases. We address the problem by introducing a dual-resolution motion planning framework which utilizes a convex task region decomposition method, with each resolution tuned to efficient computation for their respective roles. Concretely, this dual-resolution approach enables a global planner to explore the low-dimensional decomposed task-space regions toward the goal, then a local planner computes a path in high-dimensional constrained configuration space. We demonstrate the proposed method in several simulations, where the robot team transports the object toward the goal in the obstacle-rich environments.

关键词： Manifolds Conferences computational modeling Kinematics System recovery Manipulators Planning

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Particle Computation: Device Fan-out and Binary Memory

Particle Computation: Device Fan-out and Binary Memory

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IEEE international Conference on robotics and automation (ICRA)

作者： Shad, Hamed Mohtasham Morris-Wright, Rose Demaine, Erik D. Fekete, Sandor P. Becker, Aaron T. MIT Comp Sci & Artificial Intelligence Lab 77 Massachusetts Ave Cambridge MA 02139 USA TU Braunschweig Dept Comp Sci D-38106 Braunschweig Germany Univ Houston Dept Elect & Comp Engn Houston TX 70004 USA

ISBN: (纸本)9781479969234

We present fundamental progress on the computational universality of swarms of micro-or nano-scale robots in complex environments, controlled not by individual navigation, but by a uniform global, external force. Consider a 2D grid world, in which all obstacles and robots are unit squares, and for each actuation, robots move maximally until they collide with an obstacle or another robot. In previous work, we demonstrated components of particle computation in this world, designing obstacle configurations that implement AND and OR logic gates: by using dual-rail logic, we designed NOT, NOR, NAND, XOR, XNOR logic gates. However, we were unable to design a FAN-OUT gate, which is necessary for simulating the full range of complex interactions that are present in arbitrary digital circuits. In this work we resolve this problem by proving unit-sized robots cannot generate a FAN-OUT gate. On the positive side, we resolve the missing component with the help of 2 x 1 robots, which can create fan-out gates that produce multiple copies of the inputs. Using these gates we are able to establish the full range of computational universality as presented by complex digital circuits. As an example we connect our logic elements to produce a 3-bit counter. We also demonstrate how to implement a data storage element.

关键词： Robots

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