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IEEE international Conference on robotics and automation (ICRA)

作者： Zhang, Weijian Wang, Jianshu Yu, Yang Polixir Ai Nanjing Peoples R China Nanjing Univ Sch Artificial Intelligence Natl Key Lab Novel Software Technol Nanjing Peoples R China

ISBN: (纸本)9798350384581;9798350384574

Distributional Reinforcement Learning (DRL) not only endeavors to optimize expected returns, but also strives to accurately characterize the full distribution of these returns, a key aspect in enhancing risk-aware decision-making. Previous DRL implementations often inappropriately treat statistical estimations as concrete samples, which undermines the integrity of learning. While several studies have addressed this issue, they frequently give rise to new complications, including computational burdens and diminished stochastic behavior. In our work, we present a novel DRL framework that leverages the Gaussian mixture model to adeptly depict the distribution of returns. This approach ensures precise, authentic sampling critical for robust learning, while also preserving computational tractability. Through extensive evaluation on a diverse array of 59 Atari games, our method not only surpasses the efficacy of prior DRL algorithms but also presents formidable competition to contemporary top-tier RL algorithms, signifying a substantial advancement in the field.

关键词： Adversarial machine learning

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GEOMETRICAL FUSION METHOD FOR MULTISENSOR ROBOTIC SYSTEMS

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1989 IEEE international CONF ON robotics AND automation : robotics IN UNSTRUCTURED ENVIRONMENTS

作者： NAKAMURA, Y XU, YT Univ of California Santa Barbara CA USA

ISBN: (纸本)0818619384

A general statistical fusion method motivated by the geometry of uncertainties is proposed for robotic systems with multiple sensors. The treatment of nonlinearity is generalized so as to include both the structural nonlinearity and the computational nonlinearity. First, assuming Gaussian noise additive to the sensory data, the uncertainty ellipsoid associated with the covariance matrix of the error of the sensory information is defined. Second, the optimal fusion is defined as the one, among all the possible linear combinations of sensory information, that minimizes the geometrical volume of the ellipsoid. The resultant fusion equation coincides with those obtained by Bayesian inference, Kalman filter theory, and the weighted least-squares estimation. Finally, the method is extended to include the fusion of partial information.

关键词： robotics

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Active Inference for Integrated State-Estimation, Control, and Learning

Active Inference for Integrated State-Estimation, Control, a...

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IEEE international Conference on robotics and automation (ICRA)

作者： Baioumy, Mohamed Duckworth, Paul Lacerda, Bruno Hawes, Nick Univ Oxford Oxford Robot Inst Oxford England

ISBN: (纸本)9781728190778

This work presents an approach for control, state-estimation and learning model (hyper)parameters for robotic manipulators. It is based on the active inference framework, prominent in computational neuroscience as a theory of the brain, where behaviour arises from minimizing variational free-energy. First, we show there is a direct relationship between active inference controllers, and classic methods such as PID control. We demonstrate its application for adaptive and robust behaviour of a robotic manipulator that rivals state-of-the-art. Additionally, we show that by learning specific hyperparameters, our approach can deal with unmodeled dynamics, damps oscillations, and is robust against poor initial parameters. The approach is validated on the 'Franka Emika Panda' 7 DoF manipulator. Finally, we highlight limitations of active inference controllers for robotic systems.

关键词： PI control Conferences computational neuroscience Estimation Robustness Filtering theory PD control

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Bayesian Multimodal Integration in a Robot Replicating Human Head and Eye Movements

Bayesian Multimodal Integration in a Robot Replicating Human...

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IEEE international Conference on robotics and automation (ICRA)

作者： Antonelli, Marco del Pobil, Angel P. Rucci, Michele Univ Jaume 1 Robot Intelligence Lab Castellon de La Plana 12070 Spain Boston Univ Dept Psychol & Brain Sci Boston MA 02215 USA Boston Univ Grad Program Neurosci Boston MA 02215 USA

ISBN: (纸本)9781479936854

Autonomous robots need to make sense of their surroundings, recognize objects, detect and, possibly, identify the people around them. Visual perception would be ideally suited for these tasks. Yet, visual perception remains one of the limiting factors of modern robotics: artificial vision systems tend to perform poorly in normal environments, where the scene and the illumination conditions are unpredictable. Evolution has faced similar problems, leading to surprisingly accurate visual capabilities, even in species with very small brains. We argue that the success of biological perception systems relies on three fundamental computational principles: (a) the continual coupling of perception and behavior;(b) the resulting emergence of multimodal cues;(c) and their efficient integration. Building on these computational principles, we describe a humanoid robot that emulates the dynamic strategy by which humans examine a visual scene. The proprioceptive and visual depth cues resulting from this strategy are integrated in statistically optimal manner into a unified representation. We show that this approach yields accurate and robust 3D representations of the observed scene.

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THE APPLICATION OF robotics TO FLUOROMETRIC AND ISOTOPIC ANALYSES OF URANIUM

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CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 1993年第2-3期21卷 223-227页

作者： HINTON, ER HANZELKA, CC HOWARD, GG Analytical Services Organization Oak Ridge Y-12 Plant Martin Marietta Energy Systems Inc. P.O. Box 2009 Building 9995 MS-8189 Oak Ridge TN 37830-8189 USA

Two laboratory robots provide analytical support to two laboratories within the Analytical Services Organization of the Oak Ridge Y-12 Plant. One system prepares uranium metals and oxides for isotopic analysis by thermal ionization mass spectrometry. The second system prepares and analyzes air filter samples for uranium content. The robots have proven to be excellent assets to the laboratories in productivity improvement, waste reduction, and personnel safety. robotics and automation will continue to provide substantial benefits to future analytical methodology within the Y-12 Plant.

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Parameterizable and Jerk-Limited Trajectories with Blending for Robot Motion Planning and Spherical Cartesian Waypoints

Parameterizable and Jerk-Limited Trajectories with Blending ...

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IEEE international Conference on robotics and automation (ICRA)

作者： Lin, Jianjie Rickert, Markus Knoll, Alois Tech Univ Munich Robot Artificial Intelligence & Real Time Syst Dept Informat Munich Germany

ISBN: (纸本)9781728190778

This paper presents two different approaches to generate a time local-optimal and jerk-limited trajectory with blends for a robot manipulator under consideration of kinematic constraints. The first approach generates a trajectory with blends based on the trapezoidal acceleration model by formulating the problem as a nonlinear constraint and a non-convex optimization problem. The resultant trajectory is locally optimal and approximates straight-line movement while satisfying the robot manipulator's constraints. We apply the bridged optimization strategy to reduce the computational complexity, which borrows an idea from model predictive control by dividing all waypoints into consecutive batches with an overlap of multiple waypoints. We successively optimize each batch. The second approach is a combination of a trapezoidal acceleration model with a 7-degree polynomial to form a path with blends. It can be efficiently computed given the specified blending parameters. The same approach is extended to Cartesian space. Furthermore, a quaternion interpolation with a high degree polynomial under consideration of angular kinematics is introduced. Multiple practical scenarios and trajectories are tested and evaluated against other state-of-the-art approaches.

关键词： Interpolation computational modeling Quaternions Kinematics Trajectory Time factors computational complexity

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Bridging the Gap between Robotic Applications and computational intelligence in Domestic robotics

Bridging the Gap between Robotic Applications and Computatio...

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IEEE symposium Series on computational intelligence (SSCI)

作者： Zhong, Junpei Han, Ting Lotfi, Ahmad Cangelosi, Angelo Liu, Xiaofeng Nottingham Trent Univ Sch Sci & Technol Nottingham NG11 8NS England AIST Artificial Intelligence Res Ctr Aomi 2-3-26 Tokyo 1350064 Japan Univ Manchester Sch Comp Sci Manchester M13 9PL Lancs England Hohai Univ Coll IoT Engn Changzhou 213022 Peoples R China

ISBN: (纸本)9781728124858

With the speedy development of hardware (e.g., high performance computing, smaller and cheaper sensors) and software (e.g., deep learning techniques and interaction technologies), robotic products and IoT devices have gradually become accessible to household users. Typical application scenarios of domestic robots include: 1) Providing physical assistance such as floor vacuuming;2) Providing social assistance to answer questions;and 3) Providing education and cognitive assistance such as offering partnerships. In this paper, we provide a brief overview of available domestic robots, particularly focusing on the services they provide and corresponding computational techniques incorporated in these services. We first provide an overview of available commercial domestic robots and state-of-the-art computational intelligence techniques, then discuss the gap between current robotic systems and advanced computational techniques. Finally, we analyze what are the next developmental stages for these techniques with the emergence and development of the domestic robotic platforms.

关键词： domestic robotics intelligent robotics machine learning smart Home interactive robotics service robotics

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Real-time robotic agent based on emotions

Real-time robotic agent based on emotions

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10th international symposium on robotics and Applications held at the 6th Biannual World automation Congress

作者： Domínguez, C Hassan, H Crespo, A Univ Politecn Valencia DISCA Valencia 46071 Spain

ISBN: (纸本)1889335215

Emotional systems are being considered with renewed interests as powerful computational models to design better and more intelligent robots. The aim of the work presented in this paper is to design a real-time agent based on emotions and motivations to produce behaviors that are consistent with intelligent performance in the real world. The emotional agent that will be described is founded on three main entities: concepts, emotions and conscious processes. The concepts and conscious processes are data and processes respectively. The conscience help the data and processes to organise their life cycle. The emotions adjust the motivations of the processes based on the confidence of the concepts to satiate the agent desires.

关键词： agent emotion motivation intelligence robotics behaviour real-time

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Computing with a Muscular-Hydrostat System

Computing with a Muscular-Hydrostat System

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IEEE international Conference on robotics and automation (ICRA)

作者： Nakajima, Kohei Hauser, Helmut Kang, Rongjie Guglielmino, Emanuele Caldwell, Darwin G. Pfeifer, Rolf Univ Zurich Dept Informat Artificial Intelligence Lab CH-8050 Zurich Switzerland Istituto Italiano Tecnologia Dept Adv Robot I-16113 Genoa Italy

ISBN: (纸本)9781467356411;9781467356435

Octopus arms, as well as elephant trunks, squid tentacles, and vertebrate tongues are termed muscular-hydrostats. In such structures, the volume of the organ remains constant during their motions, enabling diverse, complex, and highly controlled movements without the support of a skeleton. Such flexible structures show major advantages over articulated arms that have a rigid skeleton and joints. These advantages have been attracting roboticists aiming to apply these material properties to soft robot controls. In this paper, we show that the muscular-hydrostat system itself has the computational capacity to achieve a complex nonlinear computation. By using a 3D dynamic simulator of the system inspired by the octopus, we actually demonstrate that the system is capable of emulating complex nonlinear dynamical systems by exploiting its elastic body dynamics as a computational resource. In addition, we systematically analyze its computational power in terms of memory capacity, and show that the system has an intrinsic and characteristic short term memory profile. Finally, the implications for soft robot control and future application scenarios are discussed.

关键词： biomechanics elasticity nonlinear dynamical systems robot dynamics

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Fast Estimation of Multidimensional Regression Functions 17

Fast Estimation of Multidimensional Regression Functions

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17th international Conference on Control, automation, robotics and Vision (ICARCV)

作者： Galkowski, Tomasz Krzyzak, Adam Dziwinski, Piotr Czestochowa Tech Univ Inst Computat Intelligence Armii Krajowej 36 Czestochowa Poland Concordia Univ Dept Comp Sci & Software Engn Montreal PQ H3G 1M8 Canada

ISBN: (纸本)9781665476874

Various methods for fitting an unknown functions from the set of noisy measurements are applicable to a wide variety of problems. Among them, the nonparametric algorithms based on the Parzen kernel are willingly used. In the article, we propose a novel and very effective numerical simplification in Parzen approach leading to a significant reduction in computation time. The algorithm is basically developed for multidimensional case. The two-dimensional version of the method is explained in details and analysed. computational complexity and speed of convergence of the algorithm are studied. Some applications for solving real problems with our algorithms are presented.

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