关键词： Task analysis   Robots   Path planning   Automobiles   Scheduling   Genetic algorithms   Scheduling algorithms   Genetic algorithm   high-density automatic parking   multirobot systems   optimal scheduling algorithm  

摘要： With the process of urbanization, the problem of insufficient parking spaces has become prominent. Adopting a high-density parking lot with parking robots can greatly improve the land utilization rate of the parking lot. This article tackles the multiple parking robots scheduling problem of high-density layout parking lots, including task execution sequence decision, robot allocation, and cooperative path planning. First, we mathematically describe the parking robot scheduling problem. Existing approximation algorithms are often far from the optimal solution. This article proposes an improved genetic algorithm and a time-enhanced A* path planning algorithm for high-density parking lots. The improved genetic algorithm can efficiently search task execution sequence and robot allocation and converge to the optimal solution even in large-scale complex scenarios. Meanwhile, the time-enhanced A* algorithm takes a new dimension "the time" into consideration, together with the distance, and security factors, to solve the multi-parking-robot path planning problem. Simulation experiments show that our algorithm can improve scheduling performance in many aspects such as task execution time, driving distance, and security in large-scale high-density parking lots. This article provides an efficient and convenient scheduling solution for the implementation of the high-density unmanned parking lot.

ISBN: (纸本)9787030691842

摘要： 本书全面深入地阐述了旋量理论与李群、李代数理论及其关联关系，反映了李群、李代数与机器人机构学相结合的最新理论研究成果。全书共9章，第一章为绪论。第二章到第四章主要讲述了旋量、李群、李代数等数学理论，揭示了刚体位移的固有特性以及与有限位移旋量和李群的内在统一性。第五章介绍了旋量理论在机器人运动学的应用实例。为了更充分地展示现代数学在机器人学研究中的重要意义，根据作者在机器人学理论上的研究进展，第六章到第八章分别阐述了机器人的质心运动学、多足机器人运动规划及动力学。第九章介绍了李群李代数和旋量理论在柔性机器人机构学方面的拓展应用。

关键词： Surveys  

摘要： Accurate models of mechanical system dynamics are often critical for model-based control and reinforcement learning. Fully data-driven dynamics models promise to ease the process of modeling and analysis, but require considerable amounts of data for training and often do not generalize well to unseen parts of the state space. Combining data-driven modeling with prior analytical knowledge is an attractive alternative as the inclusion of structural knowledge into a regression model improves the model's data efficiency and physical integrity. In this article, we survey supervised regression models that combine rigid-body mechanics with data-driven modeling techniques. We analyze the different latent functions (such as kinetic energy or dissipative forces) and operators (such as differential operators and projection matrices) underlying common descriptions of rigid-body mechanics. Based on this analysis, we provide a unified view on the combination of data-driven regression models, such as neural networks and Gaussian processes, with analytical model priors. Furthermore, we review and discuss key techniques for designing structured models such as automatic differentiation. © 2021 The Authors. GAMM - Mitteilungen published by Wiley-VCH GmbH.

摘要： Presents the introductory editorial for this issue of the publication.

摘要： Presents the President’s message for this issue of the publication.

关键词： Neural adaptive control   observer-based control   prescribed performance   PID2 control   robot manipulator  

摘要： This article proposes a novel prescribed performance-based neural adaptive control scheme for robot manipulators including motor dynamics under model uncertainties without velocity, acceleration, and input current measurements. The prescribed performance function approach is used to transform a constrained tracking problem of the robot model including motor dynamics into an unconstrained third-order error model in Euler-Lagrange form which inherits all properties of the robot dynamics. Then, a projection-type neural adaptive PID2 controller (a PID controller with the second-order derivative) in conjunction with a velocity-acceleration observer is proposed. Lyapunov's direct method is used to prove that the tracking and state observation errors are semiglobally uniformly ultimately bounded and converge to a small ball around the origin with a prescribed overshoot/undershoot, convergence rate, and final tracking accuracy. Finally, simulation, experimental results on a SCARA robot and comparative studies verify that the proposed controller is effective for the joint position trajectory tracking of robot manipulators in the industrial automation with minimum measurement and hardware requirements.

关键词： Risk   Ethics   Robotics   Autonomous system   Long-term care   Systematic review  

摘要： The dwindling informal care support structure for the older population and the shortage of skilled nursing care staff propelled the rise of robotics and autonomous systems as potential solutions to meet the rising demands in long-term care. However, the nascent development in the governance of their applications could predispose older people to the negative ramifications of technological risks and ethical issues. This systematic review maps out four technological risks and five ethical issues in the deployment of robotics and autonomous systems in long-term care. Safety, privacy, liability, and adverse employment consequences to the existing nursing care workers were identified as major technological risks;while loss of autonomy, loss of human interaction and social connectedness, objectification and infantilisation, deception and social justice were identified as five major ethical issues related to the deployment of robotics and autonomous systems in long-term care. This review also identified antagonistic interactions between some of the technological risks and ethical issues that could offset each other. Findings from the review have implications for advancing knowledge on the governance of robotics in long-term care. Policy formulations and implementations would need to account for intricate issues that could arise from technological risks, ethical issues and their paradoxical interactions.

关键词： Strain   Robots   Manipulator dynamics   Heuristic algorithms   Numerical models   Kinematics   Soft robotics   Cosserat beams   direct   inverse dynamics formulation   dynamics   modeling   control   and learning for soft robots  

摘要： In this article, we propose a new dynamic model of Cosserat beams in view of its application to continuum and soft robotics manipulation and locomotion. In contrast to usual approaches, it is based on the nonlinear parameterization of the beam shape by its strain fields and their reduction on a functional basis of strain modes. While remaining geometrically exact, the approach provides us with a minimal set of ordinary differential equations in the usual Lagrange matrix form that can be exploited for analysis and control design. Inspired from rigid robotics, the calculation of the matrices of this Lagrangian model is performed with a new reduced inverse Newton-Euler algorithm. To assess the approach, this Lagrangian model is compared against a well-validated finite element method through several benches of nonlinear structural statics and dynamics.

关键词： Accuracy   Binary regression model   Latent clusters   Offensive power rating   Winning margin power rating  

摘要： Since the inception of the FIRST Robotics Competition (FRC) and its special playoff system, robotics teams have longed to appropriately quantify the strengths of their designed robots. The FRC includes a playground draft-like phase (alliance selection), arguably the most game-changing part of the competition, in which the top-8 robotics teams in a tournament based on the FRC's ranking system assess potential alliance members for the opportunity of partnering in a playoff stage. In such a three-versusthree competition, several measures and models have been used to characterize actual or relative robot strengths. However, existing models are found to have poor predictive performance due to their imprecise estimates of robot strengths caused by a small ratio of the number of observations to the number of robots. A more general regression model with latent clusters of robot strengths is, thus, proposed to enhance their predictive capacities. Two effective estimation procedures are further developed to simultaneously estimate the number of clusters, clusters of robots, and robot strengths. Meanwhile, some measures are used to assess the predictive ability of competing models, the agreement between published FRC measures of strength and model-based robot strengths of all, playoff, and FRC top-8 robots, and the agreement between FRC top-8 robots and model-based top robots. Moreover, the stability of estimated robot strengths and accuracies is investigated to determine whether the scheduled matches are excessive or insufficient. In the analysis of qualification data from the 2018 FRC Houston and Detroit championships, the predictive ability of our model is also shown to be significantly better than those of existing models. Teams who adopt the new model can now appropriately rank their preferences for playoff alliance partners with greater predictive capability than before. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Robotics and Automation   Artificial Intelligence   Computer Imaging   Vision   Pattern Recognition and Graphics   Control   Robotics   Mechatronics