手功能康复机器人的鲁棒控制研究

以手功能康复机器人为研究对象,对被控对象建立数学模型,推导鲁棒控制器,基于simMechanics建立仿真模型,实现手功能康复机器人的鲁棒控制系统。考虑到手功能康复机器人是帮助偏瘫患者进行康复训练并最大限度地诱发患肢的主动作用,控制器中加入偏瘫患者的主动作用函数。控制系统在MATLAB／Simulink的环境下仿真,结果表明所设计的鲁棒控制器能适应不同程度的偏瘫患者,具有较佳的动态特性和很强的鲁棒性能。     

Robotic U-shaped assembly line balancing using particle swarm optimization

Automation in an assembly line can be achieved using robots. In robotic U-shaped assembly line balancing (RUALB), robots are assigned to workstations to perform the assembly tasks on a U-shaped assembly line. The robots are expected to perform multiple tasks, because of their capabilities. U-shaped assembly line problems are derived from traditional assembly line problems and are relatively new. Tasks are assigned to the workstations when either all of their predecessors or all of their successors have already been assigned to workstations. The objective function considered in this article is to maximize the cycle time of the assembly line, which in turn helps to maximize the production rate of the assembly line. RUALB aims at the optimal assignment of tasks to the workstations and selection of the best fit robot to the workstations in a manner such that the cycle time is minimized. To solve this problem, a particle swarm optimization algorithm embedded with a heuristic allocation (consecutive) procedure is proposed. The consecutive heuristic is used to allocate the tasks to the workstation and to assign a best fit robot to that workstation. The proposed algorithm is evaluated using a wide variety of data sets. The results indicate that robotic U-shaped assembly lines perform better than robotic straight assembly lines in terms of cycle time.     

焊接机器人智能化技术研究现状与展望

机器人焊接已经成为自动化焊接的主要标志,实现机器人焊接过程智能化是机器人焊接技术发展的必然趋势。本文从焊接传感技术、焊缝跟踪技术、焊接路径规划技术与焊缝成形质量控制技术四个方面介绍机器人焊接智能化关键技术的研究现状及其面临的问题,也展望了焊接机器人智能化技术的发展趋势。     

基于晶格的人工内分泌系统模型及在多机器人系统中的应用

为了解决多机器人系统分布式控制问题,借鉴人体内分泌系统研究的理论成果,提出基于晶格的人工内分泌系统模型.该模型以环境晶格化为基础,以细胞智能化为依托,以累加激素为纽带,以靶细胞为导向,能够适应外环境的持续变化,保持内环境的相对稳定,充分体现人体内分泌系统的自组织和自修复特性.实验结果表明,无需复杂的集中控制策略,基于该...     

Development of a mobile robotic system for working in the double-hulled structure of a ship

Shipbuilding processes involve highly dangerous manual welding operations. Welding ship walls inside double-hulled structures presents a particularly hazardous environment for workers. This paper describes the “Rail Runner X” (RRX), a new robotic system that can move autonomously inside the walls of a double-hulled ship and automatically execute the required welding processes. The RRX robotic system is composed of a mobile platform and a welding robot consisting of a 3P3R serial manipulator. The robot is used to weld U-shaped trajectories located between two longitudinal stiffeners. The mobile platform enables traverse movements onto neighboring longitudinal stiffeners. The entire cross section of the robotic system is small enough to be placed inside the double-hulled structure via a conventional access hole from the outside shipyard floor. The overall engineering design process that led to the final robot solution developed is presented in this paper, including kinematic analysis data and experimental results for verifying the autonomous movement and welding performance.     

Model-free learning on robot kinematic chains using a nested multi-agent topology

This paper proposes a model-free learning scheme for the developmental acquisition of robot kinematic control and dexterous manipulation skills. The approach is based on a nested-hierarchical multi-agent architecture that intuitively encapsulates the topology of robot kinematic chains, where the activity of each independent degree-of-freedom (DOF) is finally mapped onto a distinct agent. Each one of those agents progressively evolves a local kinematic control strategy in a game-theoretic sense, that is, based on a partial (local) view of the whole system topology, which is incrementally updated through a recursive communication process according to the nested-hierarchical topology. Learning is thus approached not through demonstration and training but through an autonomous self-exploration process. A fuzzy reinforcement learning scheme is employed within each agent to enable efficient exploration in a continuous state–action domain. This paper constitutes in fact a proof of concept, demonstrating that global dexterous manipulation skills can indeed evolve through such a distributed iterative learning of local agent sensorimotor mappings. The main motivation behind the development of such an incremental multi-agent topology is to enhance system modularity, to facilitate extensibility to more complex problem domains and to improve robustness with respect to structural variations including unpredictable internal failures. These attributes of the proposed system are assessed in this paper through numerical experiments in different robot manipulation task scenarios, involving both single and multi-robot kinematic chains. The generalisation capacity of the learning scheme is experimentally assessed and robustness properties of the multi-agent system are also evaluated with respect to unpredictable variations in the kinematic topology. Furthermore, these numerical experiments demonstrate the scalability properties of the proposed nested-hierarchical architecture, where new agents can be recursively added in the hierarchy to encapsulate individual active DOFs. The results presented in this paper demonstrate the feasibility of such a distributed multi-agent control framework, showing that the solutions which emerge are plausible and near-optimal. Numerical efficiency and computational cost issues are also discussed.     

End‐Point Regulation and Vibration Suppression of a Flexible Robotic Manipulator

In this paper, end‐point regulation and vibration suppression are investigated for a flexible robotic manipulator subject to the external disturbances. The dynamics of the flexible robotic manipulator is represented by one partial differential equation (PDE) and five ordinary differential equations (ODEs). Based on the Lyapunov's direct method, boundary control is developed to drive the manipulator to the desired set‐point and simultaneously suppress the vibrations of the flexible manipulator. Considering the unknown spatiotemporally varying disturbance, uniform boundedness of the closed‐loop system is achieved. The control performance of the closed‐loop system is guaranteed by suitably choosing the design parameters. Simulations are provided to illustrate the effectiveness of the proposed control.     

Industrial Robot Navigation and Obstacle Avoidance Employing Fuzzy Logic

This paper proposes a novel conceptual approach based on fuzzy logic to solve the local navigation and obstacle avoidance problem for industrial 3-dof robotic manipulators. The proposed system is divided into separate fuzzy units, which control individually each manipulator link. The fuzzy rule-base of each unit combines a repelling influence, which is related to the distance between the manipulator and the nearby obstacles, with the attracting influence produced by the angular difference, between the actual and the final manipulator configuration, to generate a new actuating command for each link. It can be considered as an on-line local navigation method for the generation of instantaneous collision-free trajectories. The strategy has been successfully applied to manipulators in different simulated workspace environments providing collision-free paths. Some of the simulation results obtained are included.     

Optimal design and motion control of biomimetic robotic fish

This paper is concerned with the design, optimization, and motion control of a radiocontrolled, multi-link, free-swimming biomimetic robotic fish based on an optimized kinematic and dynamic model of fish swimming. The performance of the robotic fish is determined by both the fish＇s morphological characteristics and kinematic parameters. By applying ichthyologic theories of propulsion, a design framework that takes into consideration both mechatronic constraints in physical realization and feasibility of control methods is presented, under which a multiple linked robotic fish that integrates both the carangiform and anguilliform swimming modes can be easily developed. Taking account of both theoretic hydrodynamic issues and practical problems in engineering realization, the optimal link-lengthratios are numerically calculated by an improved constrained cyclic variable method, which are successfully applied to a series of real robotic fishes. The rhythmic movements of swimming are driven by a central pattern generator （CPG） based on nonlinear oscillations, and up-and-down motion by regulating the rotating angle of pectoral fins. The experimental results verify that the presented scheme and method are effective in design and implementation.     

Robust tracking control design for uncertain robotic systems with persistent bounded disturbances

In this study, a robust nonlinear L_∞‐gain tracking control design for uncertain robotic systems is proposed under persistent bounded disturbances. The design objective is that the peak of the tracking error in time domain must be as small as possible under persistent bounded disturbances. Since the nonlinear L_∞ ‐gain optimal tracking control cannot be solved directly, the nonlinear L_∞ ‐gain optimal tracking problem is transformed into a nonlinear L_∞ ‐gain tracking problem by given a prescribed disturbance attenuation level for the L_∞ ‐gain tracking performance. To guarantee that the L_∞ ‐gain tracking performance can be achieved for the uncertain robotic systems, a sliding‐mode scheme is introduced to eliminate the effect of the parameter uncertainties. By virtue of the skew‐symmetric property of the robotic systems, sufficient conditions are developed for solving the robust L_∞ ‐gain tracking control problems in terms of an algebraic equation instead of a differential equation. The proposed method is simple and the algebraic equation can be solved analytically. Therefore, the proposed robust L_∞ ‐gain tracking control scheme is suitable for practical control design of uncertain robotic systems. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society