Neural network impedance force control of robot manipulator

The performance of an impedance controller for robot force tracking is affected by the uncertainties in both the robot dynamic model and environment stiffness. The purpose of this paper is to improve the controller robustness by applying the neural network (NN) technique to compensate for the uncertainties in the robot model. NN control techniques are applied to two impedance control methods: torque-based and position-based impedance control, which are distinguished by the way of the impedance functions being implemented. A novel error signal is proposed for the NN training. In addition, a trajectory modification algorithm is developed to determine the reference trajectory when the environment stiffness is unknown. The robustness analysis of this algorithm to force sensor noise and inaccurate environment position measurement is also presented. The performances of the two NN impedance control schemes are compared by computer simulations. Simulation results based on a three-degrees-of-freedom robot show that highly robust position/force tracking can be achieved in the presence of large uncertainties and force sensor noise     

The Tricept robot: dynamics and impedance control

The Tricept is a novel industrial robot characterized by a hybrid kinematic design featuring a three-degrees-of-freedom (3-DOF) structure of parallel type and a 3-DOF spherical wrist. In this work the authors focus on the derivation of a dynamic model to be used for both simulation and control purposes. Two different approaches are discussed and compared in terms of inverse dynamics computation. Then, a model-based control is derived aimed at enforcing a 6-DOF impedance behavior at the end effector to manage interaction with the environment. Simulation results are presented to evaluate the accuracy of an approximate dynamic model computation as well as to test the effectiveness of the proposed impedance control strategy.     

Distributed supervisory control for multiple robot autonomous navigation performing single-robot tasks

This paper proposes two new approaches based on the Supervisory Control Theory (SCT) of Discrete Event Systems (DES) for autonomous navigation of multiple robots with single-robot tasks being assigned by a centralized scheduler. The two planning strategies differ regarding their implementation, which can be centralized or distributed. Nevertheless, both approaches share the central objective of considering the scheduler and robots as DES, allowing the use of SCT to model and control the behavior of the whole multi-robotic system. Particularly, SCT is used to gather deliberative and reactive motion planning algorithms through a structured procedure, aiming to safely navigate in cluttered, dynamic, partially-known environments. The open-loop behavior of the autonomous navigation system is modeled for both approaches. Moreover, standard supervisors are obtained for the centralized planning approach. In addition, the supervisor localization method is considered to allow a distributed planning approach. Furthermore, as a case study, real experiments considering mobile robots are carried out to corroborate the proposed framework.     

Ultra-lightweight anthropomorphic dual-arm rolling robot for dexterous manipulation tasks on linear infrastructures: A self-stabilizing system

This paper proposes the application of a very low weight (3.2 kg) anthropomorphic dual-arm system capable of rolling along linear infrastructures such as power lines to perform dexterous and bimanual manipulation tasks like the installation of clip-type bird flight diverters or conduct contact-based inspection operations on pipelines to detect corrosion or leaks. The kinematic configuration of the arms, with three joints at the shoulder and one at the elbow, allows the natural replication of the human movements to conduct these tasks, exploiting also the kinematic redundancy of the shoulder to maintain the equilibrium while perching on the line. The dynamic model of the system is derived to design a self-stabilizing controller that maintains the base of the arms at an equilibrium point. The state-dependent Riccati equation (SDRE) controller is chosen for this purpose since the system is under-actuated and the contribution of the control gain (with nonlinear optimal structure) on all states is critical. The SDRE is a nonlinear optimal controller that extends the margins of stability in comparison with linear ones. Simulation results show that the SDRE performs the regulation to the equilibrium point successfully and evidence better performance with respect to a linear quadratic regulator (LQR). The system is validated in an outdoor testbed consisting of a power line mockup, presenting experimental results to evaluate the SDRE and LQR controllers, demonstrating also the autonomous installation of clip-type bird flight diverters and the aerial deployment using a multirotor platform.     

Multi-hierarchy interaction control of a redundant robot using impedance learning

The control of robots with a compliant joint motion is important for reducing collision forces and improving safety during human robot interactions. In this paper, a multi-hierarchy control framework is proposed for the redundant robot to enable the robot end-effector to physically interact with the unknown environment, while providing compliance to the joint space motion. To this end, an impedance learning method is designed to iteratively update the stiffness and damping parameters of the end-effector with desired performance. In addition, based on a null space projection technique, an extra low stiffness impedance controller is included to improve compliant joint motion behaviour when interaction forces are acted on the robot body. With an adaptive disturbance observer, the proposed controller can achieve satisfactory performance of the end-effector control even with the external disturbances in the joint space. Experimental studies on a 7 DOF Sawyer robot show that the learning framework can not only update the target impedance model according to a given cost function, but also enhance the task performance when interaction forces are applied on the robot body.     

Adaptive impedance control with variable target stiffness for wheel-legged robot on complex unknown terrain

Wheel-legged robots operating on the ground experience real-time interactions with the complex unknown terrain, which may lead to tilting of the whole body and instability if no regulated effort is made. Maintaining a horizontal posture of the whole body with changes in the terrain geometry via impedance control (IC) that is widely used in many fields is desirable to be realized. However, because the stiffness and location of the terrain relative to the robot are not known in advance, the force-tracking error occur when using IC, which is the main cause of robot tilting. In this paper, an adaptive variable impedance control (AVIC) method is proposed to minimize the force-tracking error for the forces of each leg that are exerted on the body, thereby maintaining a horizontal posture of the whole body and improving the stability. This control method is applied by adjusting the target stiffness to compensate for terrain uncertainties. In terms of the existence of the dynamic force tracking error, the proposed control method also allows the robot to adapt to changes to track the desired force. The theoretical analysis of the stability of the AVIC was demonstrated through a stable force-tracking application. The numerical and experimental results were compared to those obtained using IC, and the proposed control method was validated on complex, unknown terrain.     

Generalized proportional integral observer based control of an omnidirectional mobile robot

This paper presents an observer based trajectory tracking control system design for an omnidirectional mobile robot with MY wheel-II. MY wheel-II is a switch wheel mechanism. Switch wheeled omnidirectional mobile robots are complicated autonomous switched nonlinear systems. In this paper, the complicated switching dynamics, unmodeled dynamics and input–output cross-couplings are considered as an unknown time-varying perturbation input vector, which is online estimated by means of a generalized proportional integral observer. The original switched nonlinear multi-input multi-output system is then reduced to three decoupled double integrators in an approximate manner. Traditional proportional derivative controllers are then applied to the decoupled double integrators. In addition, only part of the robot model information is used in the control system design. Simulation and experimental tests illustrate the effectiveness of this practical control method.     

An advanced robot system for automated diagnostic tasks throughpalpation

An approach to the design of a robot system capable of executing complex sensory-motor sequences aimed at gathering data useful for diagnostic purposes is presented. The main features of such a robot system are discussed, and its possible integration in an advanced, interactive expert system for medical diagnosis is considered. As an example of implementation of the concept of a robot system for automated diagnostic tasks, the design characteristics of a tendon-actuated, anthropomorphic finger, incorporating force and position sensors for low-level compliant motion control and skin-like sensors for tactile perception, are outlined. The hierarchical control architecture devised for managing some different diagnostic sensory-motor sequences (subroutines) is also presented     

Generalized small signal impedance for microwave BARITT diodes

A general treatment is outlined and equations are developed for the small signal impedance of microwave teach-through BARITT diodes. The results are expressed in terms of "injection phase delay," φiand "drift transit," θdangles. It is shown that substantial improvements in the negative resistance and hence efficiency of such oscillators can be expected as φiis allowed to increase, but not to exceed π/2.     

Generalized impedance boundary conditions in scattering

The authors present generalized surface impedance conditions that improve medium characterization. One of the most common conditions that is often used to simulate a dielectric coating is the standard impedance boundary condition, and the improved boundary condition discussed can be viewed as a generalization of this, distinguished by the presence of higher-order derivatives of the field. By virtue of the derivatives, the conditions are less local in character, and the additional degrees of freedom can be used to better simulate the material properties of a surface. Following a review of the standard impedance condition, the new conditions are introduced. Several forms are presented, each with coefficients which are functions of the geometry and material properties of the surface. The applications of these to a variety of scattering problems are then discussed     

Task-oriented force control of parallel link robot for the assembly of segments of a shield tunnel excavation system

This paper proposes a task-oriented force control system for the assembly of segments of a shield tunnel excavation system. First, we design a generalized coordinate system referred to as a task-oriented coordinate system, so that the position and orientation of a segment can be adjusted compliantly according to the external force from existing segments with which the segment is assembled together. Then, a hybrid position/force control algorithm is designed for a parallel link robot with hydraulic actuators. The system is experimentally applied to the assembly of honey-comb shaped segments. The experimental results illustrate the validity of the proposed system.     

Generalized convolution as a tool for the multi-dimensional filtering tasks

In this paper the so-called generalized convolution, being in fact an adequate adaptation of the well known circular convolution concept to any invertible block-transform, is proposed, developed, and analysed. First the proposed idea is summarized for a one-dimensional case. Then it is extended to multidimensional problems. The presented generalized convolution concept is based on the earlier A-convolution. This idea is recalled at the beginning and a set of techniques for studying the dependence of the respective coefficients on the arbitrary transform, is suggested. The generalized convolution matrix, being an extension of that for the circular convolution, is introduced and adapted to an arbitrary invertible transform. The filtering problem is then defined and presented in the transform domain. The multidimensional analysis starts with two-dimensional problems, then it is continued with formulas for multidimensional filtering tasks. The paper is illustrated with examples computed for twenty carefully selected transforms. Among them are Haar, Hadamard, Hartley, Karhunen-Loeve and a family of 16 discrete trigonometric transforms.     

视觉引导的装配机器人平面定位补偿方法

为了提高选择顺应性装配机器手臂（SCARA）机器人平面定位的精度,采用网格模型结合最小距离误差逼近的方法,首先构建SCARA机器人平面定位的简化模型,概述网格模型构建原理,然后通过视觉采集机器人末端第1次到达的实际点与期望点相对位置关系,构建可变参量的起始网格模型,再采用最小距离误差逼近,求解下一步构建可变参量网格模型起始点,最后由期望点在网格模型中位置分布情况决定模型粒度点的收敛更新方向。结果表明,视觉引导的定位补偿策略弥补了因模型不精准而造成的平面定位精度不高的现象;空间插值补偿法定位精度为1mm~3mm,平面定位补偿精度较之有较大提高。该方法调节的参量单一、机器末端移动次数明确、工业应用性强。     

TerminatorBot: a novel robot with dual-use mechanism for locomotion and manipulation

As part of a massively distributed heterogeneous system, TerminatorBot, a novel, centimeter-scale crawling robot, has been developed to address applications in surveillance, search-and-rescue, and planetary exploration. Its two three-degree-of-freedom arms, which stow inside the cylindrical body for ballistic deployment and protected transport, comprise a dual-use mechanism for manipulation and locomotion. The intended applications require a small, rugged, and lightweight robot, hence, the desire for dual use. TerminatorBot's unique mechanism provides mobility and fine manipulation on a scale currently unavailable. To facilitate manipulation, we have also developed a specialized force/torque sensor. This new sensor design has a biased distribution of flexures, which equalizes force and torque sensitivities at the operational point. This work describes the mechanism and design of TerminatorBot, the specialized force/torque sensor, and the mechanism-specific gaits.     

A disturbance observer for robot manipulators with application toelectronic components assembly

The success of robotic assembly for odd form electronic components depends heavily on the ability to monitor and control the insertion force. For this purpose, a joint disturbance observer for robot manipulators is presented to estimate the reaction force due to component misinsertion. The derivation is presented in the time domain for a multi-degree-of-freedom manipulator without making the SISO linear system assumption. Based on the internal model control (IMC) concept, this observer is simple in structure. It is in the form of an integral controller and only requires measurements of joint position and velocity signals to be implemented. The observed perturbation signal includes the effects of model uncertainties as well as reaction force against the environment. Careful trajectory planning and detailed friction modeling are performed to enhance accuracy of the deduced reaction force. Experiments conducted on a SCARA robot for the insertion of PCB components demonstrated the performance of the proposed disturbance observer     

Supervisory control of remote manipulation

The relatively short distances to be spanned in using the manipulators presently available permit real-time control systems, frequently employing direct linkages. The advent of space flight necessitates the design of manipulation systems that can perform complicated tasks, on the moon and beyond, upon command from earth. Such a design must compensate for the communications time delay due to the distances involved and also for a difference in environment not directly observable by the human operator. The answer to the problem seems to lie in a computer-controlled remote unit, capable of making limited decisions of its own but supervised from home base.     

A CNN-based chip for robot locomotion control

In this paper, the paradigm of emergent computation is applied to locomotion control in legged robots: the locomotion gait is the result of self-organization of a network of locally coupled nonlinear oscillators. This means to adopt the biological paradigm of central pattern generator (CPG), implemented by using cellular neural networks (CNNs). The whole control strategy is hybrid in the sense that the gait generation is accomplished by a fully analog CNN, while a simple logic unit modulates the behavior of the CNN-based CPG, so that the strategy is suitable to eventually include sensory feedback. The design of a VLSI chip implementing the CNN-based CPG and some experimental results on the chip are presented. The chip is designed using a switched-capacitor technique, fundamental to obtain in a simple and direct way some key features of the hybrid control discussed. The experimental results confirm the suitability of the approach.     

Articulated hybrid mobile robot mechanism with compounded mobility and manipulation and on-board wireless sensor/actuator control interfaces

This paper presents the development of a remotely operated mobile robot system with a hybrid mechanism whereby the locomotion platform and manipulator arm are designed as one entity to support both locomotion and manipulation interchangeably. The mechanical design is briefly described as well as the dynamic simulations used to analyze the robot mobility and functionality. As part of the development, this paper mainly focuses on a new generalized control hardware architecture based on embedded on-board wireless communication network between the robot’s subsystems. This approach results in a modular control hardware architecture since no wire connections are used between the actuators and sensors in each of the mobile robot subsystems and also provides operational fault-tolerance. The effectiveness of this approach is experimentally demonstrated and validated by implementing it in the hybrid mobile robot system. The new control hardware architecture and mechanical design demonstrate the qualitative and quantitative performance improvements of the mobile robot in terms of the new locomotion and manipulation capabilities it provides. Experimental results are presented to demonstrate new operative tasks that the robot was able to accomplish, such as traversing challenging obstacles, and manipulating objects of various capacities; functions often required in various challenging applications, such as search and rescue missions, hazardous site inspections, and planetary explorations.     

运动控制与机器人

本文介绍了机器人的分类以及各种应用方向,分析了不同运动控制在机器人上的应用与发展现状。     

Client-server-based mobile robot control

A control architecture for an autonomous mobile robot usually consists of two components: (1) intelligent control software and (2) an operating system for resource access. From the point of view of a computer scientist, it is desirable to achieve a certain level abstraction from the resource (be it sensor or effector). Here, this is achieved by introducing a client-server framework for realizing abstract resource access and intelligent control. Hardware details are hidden in a middleware layer, which is inserted in between operating system and applications. In this paper, we present the most important features of our client-server approach. The servers decouple hardware and software dependencies. Communication is realized through the use of classes, offering a wide variety of client-server interaction. Event-driven servers and clients lead to quick responses in dynamic environments. Our approach gives reusability, portability, testability, and maintainability through data abstraction. It was successfully applied in our experimental platform ARS