Zhijiang Du

Development of Search-and-rescue Robots for Underground Coal Mine Applications

Rescue missions after coal mine accidents are highly risky and sometimes impossible for rescuers to perform. To decrease the risk to rescuers, two generations of tracked mobile robots have been designed and developed to replace the rescuers. In this paper, we present the design iterations with experiments carried out in training sites for rescuers and in working coal mines, and we summarize the design and development experiences of the mobile robots for such rescue missions. In coal mine rescue robots, the explosion-proof and waterproof designs are adapted to the explosive and wet environments, while the suspension systems are adapted to the unstructured working environments. The design and development experiences may provide a reference for designing and developing future mobile robot systems for coal mine accident rescue missions.

PSO-SVM-Based Online Locomotion Mode Identification for Rehabilitation Robotic Exoskeletons

Locomotion mode identification is essential for the control of a robotic rehabilitation exoskeletons. This paper proposes an online support vector machine (SVM) optimized by particle swarm optimization (PSO) to identify different locomotion modes to realize a smooth and automatic locomotion transition. A PSO algorithm is used to obtain the optimal parameters of SVM for a better overall performance. Signals measured by the foot pressure sensors integrated in the insoles of wearable shoes and the MEMS-based attitude and heading reference systems (AHRS) attached on the shoes and shanks of leg segments are fused together as the input information of SVM. Based on the chosen window whose size is 200 ms (with sampling frequency of 40 Hz), a three-layer wavelet packet analysis (WPA) is used for feature extraction, after which, the kernel principal component analysis (kPCA) is utilized to reduce the dimension of the feature set to reduce computation cost of the SVM. Since the signals are from two types of different sensors, the normalization is conducted to scale the input into the interval of [0, 1]. Five-fold cross validation is adapted to train the classifier, which prevents the classifier over-fitting. Based on the SVM model obtained offline in MATLAB, an online SVM algorithm is constructed for locomotion mode identification. Experiments are performed for different locomotion modes and experimental results show the effectiveness of the proposed algorithm with an accuracy of 96.00% ± 2.45%. To improve its accuracy, majority vote algorithm (MVA) is used for post-processing, with which the identification accuracy is better than 98.35% ± 1.65%. The proposed algorithm can be extended and employed in the field of robotic rehabilitation and assistance.

A new fuzzy intelligent obstacle avoidance control strategy for wheeled mobile robot

Obstacle avoidance is the basic requirement for any autonomous mobile robot. Fuzzy intelligent obstacle avoidance strategy is proposed in this paper for the wheeled mobile robot tracking a target in the environment with obstacles, which is composed of two fuzzy logic controllers and an intelligent coordinator. Run-to-goal fuzzy controller makes the robot approach the target when there are no obstacles in the environment; Fuzzy obstacle controller will generate obstacle avoidance commands according to target orientation information and obstacle information when the robot detecting obstacles via its onboard sensors. Intelligent coordinator is designed to coordinate the two actions mentioned above to generate robots ultimate control command. Ultimately, the robot tracks the target and realizes obstacle avoidance meanwhile. Simulations and experiments on robot platform validate the effectiveness proposed by the paper.

Active disturbance rejection control based human gait tracking for lower extremity rehabilitation exoskeleton

This paper presents an active disturbance rejection control (ADRC) based strategy, which is applied to track the human gait trajectory for a lower limb rehabilitation exoskeleton. The desired human gait trajectory is derived from the Clinical Gait Analysis (CGA). In ADRC, the total external disturbance can be estimated by the extended state observer (ESO) and canceled by the designed control law. The observer bandwidth and the controller bandwidth are determined by the practical principles. We simulated the proposed methodology in MATLAB. The numerical simulation shows the tracking error comparison and the estimated errors of the extended state observer. Two experimental tests were carried out to prove the performance of the algorithm presented in this paper. The experiment results show that the proposed ADRC behaves a better performance than the regular proportional integral derivative (PID) controller. With the proposed ADRC, the rehabilitation system is capable of tracking the target gait more accurately.

Development of a wearable exoskeleton rehabilitation system based on hybrid control mode

Lower limb rehabilitation exoskeletons usually help patients walk based on fixed gait trajectories. However, it is not suitable for unilateral lower limb disorders. In this article, a hybrid training mode is proposed to be applied in rehabilitation for unilateral lower limb movement disorders. The hybrid training includes two modes, that is, the passive training mode and the active assist mode. At an early stage of the rehabilitation therapy, the passive training mode is utilized, in which microelectromechanical systems-based attitude and heading reference system is used to collect the gait trajectory of the healthy limb. The exoskeleton on the unhealthy limb will be driven to track the joint trajectory of the healthy limb. If the patient’s abilities recovered, the rehabilitation system can be switched to the active assist mode. Two force sensors are imbedded into the interface on the thigh to measure the interaction information in order to detect the patient’s initiative walking intention. In the active mode, the walking gait trajectory is modified and generated based on the gait trajectory of the healthy side via the attitude and heading reference system. In this article, a position close control loop is designed to drive the mechanical leg to help the unhealthy limb walk. Laboratory experiments are performed on a healthy human subject to illustrate the proposed approach. Experimental results show that the proposed method can be applied and extended in the passive and active rehabilitation mode for the unilateral lower limb disorders.

Development and Analysis of an Electrically Actuated Lower Extremity Assistive Exoskeleton

An electrically actuated lower extremity exoskeleton is developed, in which only the knee joint is actuated actively while other joints linked by elastic elements are actuated passively. This paper describes the critical design criteria and presents the process of design and calculation of the actuation system. A flexible physical Human-Robot-Interaction (pHRI) measurement device is designed and applied to detect the human movement, which comprises two force sensors and two gasbags attached to the inner surface of the connection cuff. An online adaptive pHRI minimization control strategy is proposed and implemented to drive the robotic exoskeleton system to follow the motion trajectory of human limb. The measured pHRI information is fused by the Variance Weighted Average (VWA) method. The Mean Square Values (MSV) of pHRI and control torque are utilized to evaluate the performance of the exoskeleton. To improve the comfort level and reduce energy consumption, the gravity compensation is taken into consideration when the control law is designed. Finally, practical experiments are performed on healthy users. Experimental results show that the proposed system can assist people to walk and the outlined control strategy is valid and effective.

An under-actuated manipulation controller based on Workspace Analysis and Gaussian Processes

The kinematic modelling has been applied to many controllers of under-actuated manipulators. Most of these studies assume that the control process is conducted within the workspace. However, as such a kinematic model cannot describe the situations when the stable grasping is violated in the real environment, these controllers may fail unexpectedly. In this paper, we propose a combination of kinematics based Workspace Analysis (WA) and Gaussian Process Classification (GPC) to model the success rates of control actions in the theoretical workspace. We also use the Gaussian Process Regression (GPR) to model the residual between the prediction of the WA and the ground truth data. We then apply this integrated model, Gaussian Processes enhanced Workspace Analysis (GP-WA), into an optimal controller. The optimal controller is implemented on a planar under-actuated gripper with two three-phalanx fingers. Two sets of simulation experiments are carried out to validate our method. The results demonstrate that the optimal manipulation controller based on GP-WA achieves high control accuracy for manipulating a wide range of objects.

Dimensional optimization of a minimally invasive surgical robot system based on NSGA-II algorithm

Based on the proposed end-effector structure of a laparoscopic minimally invasive surgical manipulator, a dimensional optimization method is investigated to enlarge the motion range of the mechanical arm in the specific target area and reduce the collision among the mechanical arms simultaneously. Both the length of the kinematics links and the overall size of the integrated system are considered in the optimization process. The NSGA-II algorithm oriented to the multi-objective optimization is utilized to calculate the Pareto solution set of the objective function. Finally, the dependence of the evaluation indexes is analysed to filter the non-inferior set, which guarantees the selection of the optimization solution.

The tip interface mechanics modeling of a bevel-tip flexible needle insertion

As a bevel-tip flexible needle is inserted through soft tissue, the asymmetry of the needle tip conducts the needle bending naturally. The needle inside the tissue can follow a desired trajectory via controlling the direction of the asymmetrical tip. If the force between the needle and the soft tissue is explicit, the needle can be controlled to escape from obstacles and reach target lesions as accurately as possible, so a mechanics modeling between the flexible needle and the soft tissue is particularly important. In this paper, based on the consideration of friction force, the interaction of needle tip and soft tissue is modeled and analyzed during the needle linear feeding and axial rotating. In the analytical model, the forces applied on the bevel tip are formulated based on the geometry of the bevel edge and material properties of soft medium. Meanwhile, the relationship between the forces generated on the bevel-tip and the major influence factors is obtained, which is described in the several figures and also further discussed in detail. The concept and approach outlined in this paper is generic which can be extended to a variety of flexible needle insertion involved applications.

Design and realization of an interactive medical images three dimension visualization system

In this paper, an interactive medical three-dimensional visualization system is realized based on VTK. This program is designed primarily for the CT images to realize such functions as reading and displaying of image files and interactive three-dimensional reconstruction. The threshold for three-dimensional reconstruction is interactively selected by marching squares algorithm (MS), which is more convenient and more interactive for three-dimensional reconstruction by marching cubes algorithm (MC) than the traditional method that the various reconstruction thresholds are simply entered based on experience. The functional stability and good human-computer interaction of this system greatly improve accuracy and scientificity of medical diagnosis and treatment planning. The system is designed based on modular, which is not only used as a separate visualization system for medical diagnosis, but also its functions will be further added and constantly improved aiming at the different surgical needs.