自主式移动机器人系统的体系结构

本文在分析已有的几中多智能体协调模型的基础上，提出了一种用于自主式移动机器人系统的多智能体协调模型（离散）事件状态模型，用于组织协调自主式移动机器人系统中的传感器、规划、控制等智能体协调工作，确保自主式移动机器人在复杂、不断变化的环境中自主行驶，并在自主式移动机器人项目中较好地发挥了作用。     

Distributed fuzzy discrete event system for robotic sensory information processing

Abstract: This paper presents a novel intelligent sensory information processing technique using a fuzzy discrete event system (FDES) for robotic control. The proposed method combines the predictive control approach of a discrete event system with the approximate reasoning aspect of fuzzy logic. It develops a supervisory control strategy for behavior-based robotic control using distributed FDES. The application of distributed FDES eliminates the formation of complex fuzzy predicates and a large fuzzy rule-base. The FDES-based approach also provides means for analyzing behavior-based decision-making using the observability and controllability of an FDES. The observability of an FDES describes uncertainties in sensory data, and the controllability of an FDES exploits uncertain state transitions in a dynamic environment. Comprehensive experiments on behavior-based mobile robot navigation are presented to authenticate the performance of the proposed methodology.     

Autonomous grasp and manipulation planning using a ToF camera

A time-of-flight camera can help a service robot to sense its 3D environment. In this paper, we introduce our methods for sensor calibration and 3D data segmentation to use it to automatically plan grasps and manipulation actions for a service robot. Impedance control is intensively used to further compensate the modeling error and to apply the computed forces. The methods are further demonstrated in three service robotic applications. Sensor-based motion planning allows the robot to move within dynamic and cluttered environment without collision. Unknown objects can be detected and grasped. In the autonomous ice cream serving scenario, the robot captures the surface of ice cream and plans a manipulation trajectory to scoop a portion of ice cream.     

Hybrid modeling and simulation for the design of an advancedindustrial robot controller

This paper proposes the application of discrete event and hybrid modeling in the architectural design of a new commercial robot controller featuring force control capabilities. A case study is considered and architectural aspects, such as distribution of functions over a multiprocessor structure, communication among processors and sensors and task scheduling and synchronization, are modeled and simulated together with the arm continuous time dynamics. In particular, the interaction between robot position control and force control has been investigated, exploiting the features of a specific simulation tool for the design and evaluation of the real-time control strategies and of the hardware/software architecture     

A discrete event framework for autonomous observation under uncertainty

In this work we establish a framework for the general problem of observation, which may be applied to different kinds of visual tasks. We construct intelligent high-level control mechanisms for active visual recognition of different processes within a hybrid dynamic system. We address the problem of observing a manipulation process in order to illustrate the ideas and motive behind our framework. We use a discrete event dynamic system as a high-level structuring technique to model the manipulation system. The formulation utilizes the knowledge about the system and the different actions in order to solve the observer problem in an efficient, stable and practical manner. The model uses different tracking mechanisms so that the observer can see the workspace of the manipulating robot. An automaton is developed for the hand/object interaction over time and a stabilizing observer is constructed. Low-level modules are developed for recognizing the visual events that causes state transitions within the dynamic manipulation system in real time. A coarse quantization of the manipulation actions is used in order to attain an active, adaptive and goaldirected sensing mechanism. The formulation provides high-level symbolic interpretations of the scene under observation. The discrete event framework is augmented with mechanisms for recovering the continuous parametric evolution of the scene under observation and for asserting the state of the manipulation agent. This work examines closely the possibilities for errors, mistakes and uncertainties in the manipulation system, observer construction process and event identification mechanisms. We identify and suggest techniques for modeling these uncertainties. Ambiguities are allowed to develop and are resolved after finite time. Error recovery mechanisms are also devised. The computed uncertainties are utilized for navigating the observer automaton state space, asserting state transitions and developing a suitable tracking mechanism.     

机器人作业的离散事件建模与控制方法

针对传统机器人控制中规划器开环的不足, 首先设计了底层的非时间参考的连续路径规划与控制方法, 使规划器的规划值基于系统的状态之上, 避免了基于时间规划的系统由于意外事件造成的损害和任务的重新规划; 在此基础上, 又建立了整个作业任务的离散事件模型, 设计了离散事件路径规划方法及控制综合方法, 实现了事件反馈的闭环, 提高了系统处理不确定事件的能力和作业的自动化程度. 最后两台PUMA560机械手搬运被识别工件的作业验证了本文算法的有效性.     

Optimality in Robot Design and Control

Extremal problems in robot engineering are studied. Decomposition of the design of control laws for manipulation robots is implemented. Algorithms for designing the robot movement trajectory in an unknown work space through estimation functions are constructed. The structure of a modeling system and design of a manipulation robot are described.     

Coordination and decentralized cooperation of multiple mobile manipulators

Mobile manipulation capabilities are key to many new applications of robotics in space, underwater, construction, and service environments. This article discusses the ongoing effort at Stanford University for the development of multiple mobile manipulation systems and presents the basic models and methodologies for their analysis and control. This work builds on four methodologies we have previously developed for fixed-base manipulation: the Operational Space Formulation for task-oriented robot motion and force control; the Dextrous Dynamic Coordination of Macro/Mini structures for increased mechanical bandwidth of robot systems; the Augmented Object Model for the manipulation of objects in a robot system with multiple arms; and the Virtual Linkage Model for the characterization and control of internal forces in a multi-arm system. We present the extension of these methodologies to mobile manipulation systems and propose a new decentralized control structure for cooperative tasks. The article also discusses experimental results obtained with two holonomic mobile manipulation platforms we have designed and constructed at Stanford University. © 1996 John Wiley & Sons, Inc.     

基于特征深度学习的机器人协调操作感知控制

为了在操作者与机器人之间实现更为稳定的负载运动状态,提出一种基于特征深度学习的机器人协调操作感知控制方法,分析机器人的协调操作原理,根据虚拟阻尼、虚拟惯量与虚拟刚度系数,构建人机协调操作模型,利用特征深度学习对模型内的神经网络进行网络信息的交互拓扑,优化机器人协调操作的感知性能.同时,减少内存占比,对人力交互信息滤波去...     

基于事件相机的机器人感知与控制综述

事件相机作为一种新型动态视觉传感器, 通过各个像素点独立检测光照强度变化并异步输出“事件流”信号, 具有数据量小、延迟低、动态范围高等优秀特性, 给机器人控制带来新的可能. 本文主要介绍了近年来涌现的一系列事件相机与无人机、机械臂和人形机器人等机器人感知与运动控制结合的研究成果, 同时聚焦基于事件相机的控制新方法、新原理以及控制效果, 并指出基于事件相机的机器人控制的应用前景和发展趋势.     

连续型机器人研究综述

连续型机器人是一种新型的仿生机器人,采用“无脊椎”的柔性结构,不具有任何离散关节和刚性连 杆．其弯曲性能优良,对障碍物众多的非结构环境和工作空间狭小的受限工作环境适应能力强,不仅可以像传统机 器人那样在其末端安装执行器以实现抓取和夹持等动作,还可以利用其整个机器人本体实现对物体的抓取．本文对 连续型机器人的仿生原理与结构特点进行了分析,介绍了连续型机器人的研究现状,并对其潜在应用领域和未来研 究工作进行了探讨和展望．     

Whole-finger manipulation with a two-fingered robot hand

This paper describes a method for whole-finger rolling manipulation using a two-fingered robot hand. 'Whole-finger' refers to the use of the complete phalangeal surface during the manipulation. An example of whole-finger manipulation by the human hand is the rolling of a pen between two fingers. The proposed method is based on a two-dimensional model for modelling an object manipulation and is derived from a study of the movement of the contact line between both fingers. Also, the method uses tactile sensor information to estimate the contact point position together with the local curvature of the object. This whole-finger dexterous manipulation is demonstrated on a prototype two-fingered hand. This 5 d.o.f. hand consists of a tendon driven index and thumb, and is equipped with force and tactile sensors. The dimensions and performance of this device are 'human-sized'. A hybrid force-position control scheme is used. The hierarchical control structure is implemented on a dual transputer system. This paper first describes the kinematic model used for whole-finger manipulation. In the second part, the main emphasis is put on the mechanical design and on the transputer-based control system.     

Application of discrete learning control to a robotic manipulator

An effective iterative learning control law is developed in discrete time domain for improving the trajectory tracking performance of robotic manipulators repeating the same task from cycle to cycle. With this method, information on the current-cycle is intentionally introduced into the learning law such that the convergence rate can be further improved. An analysis of convergence, formulated completely in discrete time, is given. Experimental results, based on implementation on a commercial robot, are also presented and discussed in the paper which demonstrated the effectiveness of the learning control method.     

A singularity-free motion control algorithm for robot manipulators—a hybrid system approach

This paper presents the design and implementation of a singularity-free tracking algorithm for robot manipulators using a hybrid system approach. A hybrid robot motion controller is designed to ensure feasible robot motion in the neighborhood of kinematic singularities. The hybrid control system has a two-layered hierarchical structure, a discrete layer and a continuous layer. The robot workspace is partitioned into subspaces based on the singular configurations of the robot. Switching between continuous controllers is involved when the robot travels across the subspaces. With the hybrid controller, the robot can work at the vicinity of singular configurations, but also can go through and stay at the singular configurations. The stability of the hybrid system is investigated using multiple Lyapunov function theory. Experimental results have demonstrated the advantages of the hybrid robot motion control method.     

Behavior-modulation technique in mobile robotics using fuzzy discrete event system

This paper presents a novel behavior-modulation technique using a fuzzy discrete event system (FDES) for behavior-based robotic control. The method exploits the multivalued feature of fuzzy logic (FL) and event-driven property of a discrete event system (DES) to generate the activity of a behavior using fuzzy state vectors. State-based prediction of an activity is accomplished using fuzzily defined event matrices. A central arbiter employs priority-based arbitration among the activity state vectors and generates new event matrices to modify the activity states of the behaviors. The method combines aspects of both command fusion and behavior arbitration. Furthermore, the proposed approach has the ability to define state-based observability and controllability to handle sensory uncertainty and environmental dynamics. Observability describes decision vagueness associated with sensory data, whereas controllability specifies undesirable state-reach within the observed environment. Real-time results of FDES-based mobile robot navigation are presented and compared against four different modulation methods to validate its superior performance.     

Deadlock-free dynamic resource assignment in multi-robot systems with multiple missions： application in wireless sensor networks

In unstructured environments, dynamic resource assignment is required for effective cooperation of robot teams. In some scenarios, robots are in charge of executing multiple missions simultaneously. This creates risks of deadlock due to the presence of shared resources among various missions. The main contribution of this paper is the development of a novel approach that combines the one-step look-ahead deadlock avoidance policy with dynamic resource assignment. The dynamic resource assignment is achieved using greedy resource assignment for multi-mission robot teams in the framework of a matrix-based discrete event controller. Simulation results are presented in MATLAB°R to discuss in detail the proposed control strategy. The paper also discusses the toolkit developed in LabVIEW°R which is used to implement this control framework using a suitable example.     

A Reactive Neuromorphic Controller for Local Robot Navigation

This paper presents and discusses a neuromorphic approach to designing a control law for locally guided robot navigation which allows for instantaneous response to the changes in the robot environment. The control algorithm is defined in the discrete domain appropriate for dedicated VLSI implementation and direct processing of discrete sensory data, such as obtained from a CCD camera. The control law is based on the principle of virtual force fields. The virtual forces (repulsive and circulation vectors) guiding the robot in the vicinity of obstacles are derived from the gradient fields associated with discrete representation of visual information. Discretization and computational tasks are assigned to parallel neuromorphic processors, which emulate the gradient operations. The particularities of discrete geometrical representations of the world and the adjustable control parameters essential for flexible and robust controller operation are discussed in detail. Finally, a detailed scheme of a tunable navigation controller specifying the parameters generated internally by the network and those that have to be provided from an external source (e.g., the operator, or a supervisory knowledge-based controller) is provided.     

电动力液压驱动四足双臂机器人的设计与实现

针对定基座机器人在复杂环境下作业能力不足的问题,研制出电动力液压四足双臂机器人,将浮动基座与双臂系统的优势有机结合,能够代替人员完成复杂环境下应急处置、工程作业等任务。详细阐述了四足双臂机器人的机械结构、机载电液动力系统、分布式控制系统以及仿真与操作训练平台的设计与实现。提出基于全身虚拟模型的足底力分配方法与足臂协调运动规划方法,实现了躯干浮动基座与双臂系统的联动,大大提升了机器人的作业能力和效率。通过搭建的仿真与操作训练平台完成单臂作业以及双臂协同作业的仿真,验证了所提出控制方法的有效性,并对机器人操作员进行操作训练。在实际样机实验中,测试了单臂抓取以及双臂协同抓取的能力,证明了四足双臂机器人能够满足复杂环境下移动作业的需求。