This paper introduces a systematic approach to identifying a physically feasible set of robot dynamics parameters. The framework consists of four steps: 1) Identification of robot dynamics parameters using least squares combined with a linear friction model. 2) Construction of a weighting matrix based on the least squares identification error, and performing weighted least squares identification combined with the linear friction model. 3) Introduction of a nonlinear friction model to fit joint friction. 4) Optimization of the remaining robot dynamics parameters to adhere to physical feasibility constraints. Various combinations of identification methods with linear or nonlinear friction models are analyzed experimentally, using a 6-DoF industrial robot and a 7-DoF collaborative robot, respectively, to demonstrate the effectiveness of the proposed recognition framework. Experimental results affirm that the proposed method provides accurate estimates of the robot joint torques while maintaining the physical feasibility of the dynamics.

Online evaluation of battery state of function (SOF) is crucial for battery management systems of autonomous mobile robots. Battery State of Charge (SOC) represents its remaining energy available, whereas internal resistance and capacity reflect its state of health (SOH). In this paper, an improved equivalent circuit model is proposed to estimate SOC, internal resistance and capacity using an unscented Kalman filter (UKF). The proposed method not only estimates SOC, but also evaluates SOH and SOF. Experimental results have shown the effectiveness of the proposed method using resistive loads and a robot prototype for inspecting power transmission line.

The purpose of inspection tasks for power transmission lines is to check running state and find damages of extra-high voltage (EHV) power transmission lines equipment. Obviously, inspection tasks are very important for normal operation of power transmission lines. So far, there are two methods for checking power transmission lines. One method is that power transmission line equipment has been checked manually by workers with a telescope on the ground. Another method is that power transmission line equipment has been inspected by helicopter with the checking devices which are thermal infrared imager, visible light camera and so on. After inspection robot configuration is described, the centroid adjustment principle of inspection robot is introduced. Then the control strategy of inspection robot is investigated. From the experiments, we find that the centroid adjustment method proposed and the control strategy presented is feasible.

This paper presents a multiple-model and Boolean logic reasoning (MMBLR) approach to detect and identify faults in the suction foot control of a climbing robot. For this control system, some fault models are easily given by kinematics equations. Moreover, the logic relations of the system states have been known in advance. Based on the combination of the multiple-model adaptive estimation (MMAE) algorithm and the Boolean logic reasoning, the MMBLR approach is properly fit for the fault detection and identification (FDI) application to the climbing robot. In the MMBLR architecture, the MMAE algorithm is used to reliably detect and identify the model-known faults. Then based on the robot's states and the results of the MMAE, other faults are detected and identified using the Boolean logic reasoning. Experimental results validated that the faults of the sensors and actuators in the suction foot control of the robot can be readily detected and identified by the MMBLR approach

The static measuring model and the deadweight compensation of a Stewart platform based force/torque sensor have been studied in this paper. Firstly, some preliminary kinematics of this sensor is presented. Coordinates attached to every links are established, and the transforming relations between link frames and other frames are derived. Then, the static measuring model and the deadweight compensation of the sensor are produced. In the modeling, forces on links are composed based on an analytic method, and the resultant forces and torques obtained can be used as the measuring model. The weight need to be compensated of the whole mechanism is divided into two parts: links weights and top platform weight. The compensation of the links weights is involved in static modeling. And the top platform weight is compensated, subsequently. Finally, some experiments are carried out, and the results verify the validity of the static measuring model and the deadweight compensation

Inspection robot with dual wheels encounters upslope and down slope, when it runs on the overhead ground wires (OGWs) which displays catenary shape. The tilt of the body of inspection robot, which is caused by the angle variation of catenary in different position, will occur during running procedure, and disenable to check vertically the transmission lines by camera. An adjustment method, which can keep the body of inspection robot in horizontal pose, is presented by the obliquitous sensor changing the length of the manipulators in this paper. In order to implement the pose adjustment, the dynamic model is established by Lagrange method. Finally, the simulation and experiment results show that the adjustment method proposed is feasible

This paper presents an obstacle-navigation control strategy for a mobile robot suspended on overhead ground wires of power transmission lines based on a novel movement mechanism. The kinematics of the mobile robot and the process of obstacle-navigation control are analyzed in detail. This paper presents to develop robot expert system using hybrid programming of C language integrated production system (CLIPS) and C language, and the robot expert system has powerful logical reasoning ability and data processing ability. The robot control modes have layered planning and direct control. This paper describes the robot expert system with hybrid architecture and analyzed decision-making of obstacle-navigation in layered planning mode in detail. The robot can learn online or offline, and when it encounter the same obstacles, it can navigate them quickly. Obstacle-navigation control is the difficult point of the type of wire-suspended robot and the expert system can instruct the mobile robot to navigate obstacles autonomously on overhead ground wires.

By converting a nonlinear problem to a linear one by means of the least square fit, a nonlinear error modeling method based on measuring data is presented. Combined with an example, some key items are pointed out during modeling. The simulation results on a parallel machine tool show that the model based on the method is of high accuracy and the error modeling method is correct and reliable. No matter what the error parameter of position and orientation is, the ideal error model would be obtained by means of the method. The accuracy of a parallel machine tool can be raised greatly by using the model to compensate the position and orientation.