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Article
Publication date: 13 August 2020

Kun Li, Shuai Ji, Guojun Niu, Yue Ai, Bo Pan and Yili Fu

Existing robot-assisted minimally invasive surgery (RMIS) system lacks of force feedback, and it cannot provide the surgeon with interaction forces between the surgical…

Abstract

Purpose

Existing robot-assisted minimally invasive surgery (RMIS) system lacks of force feedback, and it cannot provide the surgeon with interaction forces between the surgical instruments and patient’s tissues. This paper aims to restore force sensation for the RMIS system and evaluate effect of force sensing in a master-slave manner.

Design/methodology/approach

This paper presents a four-DOF surgical instrument with modular joints and six-axis force sensing capability and proposes an incremental position mode master–slave control strategy based on separated position and orientation to reflect motion of the end of master manipulator to the end of surgical instrument. Ex-vivo experiments including tissue palpation and blunt dissection are conducted to verify the effect of force sensing for the surgical instrument. An experiment of trajectory tracking is carried out to test precision of the control strategy.

Findings

Results of trajectory tracking experiment show that this control strategy can precisely reflect the hand motion of the operator, and the results of the ex-vivo experiments including tissue palpation and blunt dissection illustrate that this surgical instrument can measure the six-axis interaction forces successfully for the RMIS.

Originality/value

This paper addresses the important role of force sensing and force feedback in RMIS, clarifies the feasibility to apply this instrument prototype in RMIS for force sensing and provides technical support of force feedback for further clinical application.

Details

Industrial Robot: the international journal of robotics research and application, vol. 47 no. 6
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 25 October 2019

Fuhai Zhang, Legeng Lin, Lei Yang and Yili Fu

The purpose of this paper is to propose a variable impedance control method of finger exoskeleton for hand rehabilitation using the contact forces between the finger and…

Abstract

Purpose

The purpose of this paper is to propose a variable impedance control method of finger exoskeleton for hand rehabilitation using the contact forces between the finger and the exoskeleton, making the output trajectory of finger exoskeleton comply with the natural flexion-extension (NFE) trajectory accurately and adaptively.

Design/methodology/approach

This paper presents a variable impedance control method based on fuzzy neural network (FNN). The impedance control system sets the contact forces and joint angles collected by sensors as input. Then it uses the offline-trained FNN system to acquire the impedance parameters in real time, thus realizing tracking the NFE trajectory. K-means clustering method is applied to construct FNN, which can obtain the number of fuzzy rules automatically.

Findings

The results of simulations and experiments both show that the finger exoskeleton has an accurate output trajectory and an adaptive performance on three subjects with different physiological parameters. The variable impedance control system can drive the finger exoskeleton to comply with the NFE trajectory accurately and adaptively using the continuously changing contact forces.

Originality/value

The finger is regarded as a part of the control system to get the contact forces between finger and exoskeleton, and the impedance parameters can be updated in real time to make the output trajectory comply with the NFE trajectory accurately and adaptively during the rehabilitation.

Details

Industrial Robot: the international journal of robotics research and application, vol. 47 no. 1
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 26 August 2021

Xu Li, Yixiao Fan, Haoyang Yu, Haitao Zhou, Haibo Feng and Yili Fu

The purpose of this paper is to propose a novel jump control method based on Two Mass Spring Damp Inverted Pendulum (TMS-DIP) model, which makes the third generation of…

Abstract

Purpose

The purpose of this paper is to propose a novel jump control method based on Two Mass Spring Damp Inverted Pendulum (TMS-DIP) model, which makes the third generation of hydraulic driven wheel-legged robot prototype (WLR-3P) achieve stable jumping.

Design/methodology/approach

First, according to the configuration of the WLR, a TMS-DIP model is proposed to simplify the dynamic model of the robot. Then the jumping process is divided into four stages: thrust, ascent, descent and compression, and each stage is modeled and solved independently based on TMS-DIP model. Through WLR-3P kinematics, the trajectory of the upper and lower centroids of the TMS-DIP model can be mapped to the joint space of the robot. The corresponding control strategies are proposed for jumping height, landing buffer, jumping attitude and robotic balance, so as to realize the stable jump control of the WLR.

Findings

The TMS-DIP model proposed in this paper can simplify the WLR dynamic model and provide a simple and effective tool for the jumping trajectory planning of the robot. The proposed approach is suitable for hydraulic WLR jumping control. The performance of the proposed wheel-legged jump method was verified by experiments on WLR-3P.

Originality/value

This work provides an effective model (TMS-DIP) for the jump control of WLR-3P. The results showed that the number of landing shock (twice) and the pitch angle fluctuation range (0.44 rad) of center of mass of the jump control method based on TMS-DIP model are smaller than those based on spring-loaded inverted pendulum model. Therefore, the TMS-DIP model makes the jumping process of WLR more stable and gentler.

Details

Industrial Robot: the international journal of robotics research and application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 15 October 2020

Enbo Li, Haibo Feng, Yanwu Zhai, Zhou Haitao, Li Xu and Yili Fu

One of the development trends of robots is to enable robots to have the ability of anthropomorphic manipulation. Grasping is the first step of manipulation. For mobile…

Abstract

Purpose

One of the development trends of robots is to enable robots to have the ability of anthropomorphic manipulation. Grasping is the first step of manipulation. For mobile manipulator robots, grasping a target during the movement process is extremely challenging, which requires the robots to make rapid motion planning for arms under uncertain dynamic disturbances. However, there are many situations require robots to grasp a target quickly while they move, such as emergency rescue. The purpose of this paper is to propose a method for target dynamic grasping during the movement of a robot.

Design/methodology/approach

An off-line learning from demonstrations method is applied to learn a basic reach model for arm and a motion model for fingers. An on-line dynamic adjustment method of arm speed for active and passive grasping mode is designed.

Findings

The experimental results of the robot movement on flat, slope and speed bumps ground show that the proposed method can effectively solve the problem of fast planning under uncertain disturbances caused by robot movement. The method performs well in the task of target dynamic grasping during the robot movement.

Originality/value

The main contribution of this paper is to propose a method to solve the problem of rapid motion planning of the robot arm under uncertain disturbances while the robot is grasping a target in the process of robot movement. The proposed method significantly improves the grasping efficiency of the robot in emergency situations. Experimental results show that the proposed method can effectively solve the problem.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 1
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 1 December 2020

Rupeng Yuan, Fuhai Zhang, Yili Fu and Shuguo Wang

The purpose of this paper is to propose a robust iterative LIDAR-based pose tracking method assisted by modified visual odometer to resist initial value disturbance and…

Abstract

Purpose

The purpose of this paper is to propose a robust iterative LIDAR-based pose tracking method assisted by modified visual odometer to resist initial value disturbance and locate a robot in the environments with certain occlusion.

Design/methodology/approach

At first, an iterative LIDAR-based pose tracking method is proposed. The LIDAR information is filtered and occupancy grid map is pre-processed. The sample generation and scoring are iterated so that the result is converged to the stable value. To improve the efficiency of sample processing, the integer-valued map indices of rotational samples are preserved and translated. All generated samples are analyzed to determine the maximum error direction. Then, a modified visual odometer is introduced for error compensation. The oriented fast and rotated brief (ORB) features are uniformly sampled in the image. A local map which contains key frames for reference is maintained. These two measures ensure that the modified visual odometer is able to return robust result which compensates the error of LIDAR-based pose tracking method in the maximum error direction.

Findings

Three experiments are conducted to prove the advantages of the proposed method. The proposed method can resist initial value disturbance with high computational efficiency, give back credible real-time result in the environment with abundant features and locate a robot in the environment with certain occlusion.

Originality/value

The proposed method is able to give back real-time pose tracking results with robustness. The iterative sample generation enables the robot to resist initial value disturbance. In each iteration, rotational and translational samples are separately generated to enhance computational efficiency. The maximum error direction of LIDAR-based pose tracking method is determined by principle component analysis and compensated by the result of modified visual odometer to give back correct pose in the environment with certain occlusion.

Details

Sensor Review, vol. 41 no. 1
Type: Research Article
ISSN: 0260-2288

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Article
Publication date: 23 November 2020

Zhou Haitao, Haibo Feng, Li Xu, Songyuan Zhang and Yili Fu

The purpose of this paper is to improve control performance and safety of a real two-wheeled inverted pendulum (TWIP) robot by dealing with model uncertainty and motion…

Abstract

Purpose

The purpose of this paper is to improve control performance and safety of a real two-wheeled inverted pendulum (TWIP) robot by dealing with model uncertainty and motion restriction simultaneously, which can be extended to other TWIP robotic systems.

Design/methodology/approach

The inequality of lumped model uncertainty boundary is derived from original TWIP dynamics. Several motion restriction conditions are derived considering zero dynamics, centripedal force, ground friction condition, posture stability, control torque limitation and so on. Sliding-mode control (SMC) and model predictive control (MPC) are separately adopted to design controllers for longitudinal and rotational motion, while taking model uncertainty into account. The reference value of the moving velocity and acceleration, delivered to the designed controller, should be restricted in a specified range, limited by motion restrictions, to keep safe.

Findings

The cancelation of model uncertainty commonly existing in real system can improve control performance. The motion commands play an important role in maintaining safety and reliability of TWIP, which can be ensured by the proposed motion restriction to avoid potential movement failure, such as slipping, lateral tipping over because of turning and large fluctuation of body.

Originality/value

An inequation of lumped model uncertainty boundary incorporating comprehensive errors and uncertainties of system is derived and elaborately calculated to determine the switching coefficients of SMC. The motion restrictions for TWIP robot moving in 3D are derived and used to impose constraints on reference trajectory to avoid possible instability or failure of movement.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 1
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 27 April 2020

Yongxiang Wu, Yili Fu and Shuguo Wang

This paper aims to design a deep neural network for object instance segmentation and six-dimensional (6D) pose estimation in cluttered scenes and apply the proposed method…

Abstract

Purpose

This paper aims to design a deep neural network for object instance segmentation and six-dimensional (6D) pose estimation in cluttered scenes and apply the proposed method in real-world robotic autonomous grasping of household objects.

Design/methodology/approach

A novel deep learning method is proposed for instance segmentation and 6D pose estimation in cluttered scenes. An iterative pose refinement network is integrated with the main network to obtain more robust final pose estimation results for robotic applications. To train the network, a technique is presented to generate abundant annotated synthetic data consisting of RGB-D images and object masks in a fast manner without any hand-labeling. For robotic grasping, the offline grasp planning based on eigengrasp planner is performed and combined with the online object pose estimation.

Findings

The experiments on the standard pose benchmarking data sets showed that the method achieves better pose estimation and time efficiency performance than state-of-art methods with depth-based ICP refinement. The proposed method is also evaluated on a seven DOFs Kinova Jaco robot with an Intel Realsense RGB-D camera, the grasping results illustrated that the method is accurate and robust enough for real-world robotic applications.

Originality/value

A novel 6D pose estimation network based on the instance segmentation framework is proposed and a neural work-based iterative pose refinement module is integrated into the method. The proposed method exhibits satisfactory pose estimation and time efficiency for the robotic grasping.

Details

Industrial Robot: the international journal of robotics research and application, vol. 47 no. 4
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 13 December 2017

Shuizhong Zou, Bo Pan, Yili Fu and Shuixiang Guo

The purpose of this paper is to propose a control algorithm to improve the backdrivability performance of minimally invasive surgical robotic arms, so that precise manual…

Abstract

Purpose

The purpose of this paper is to propose a control algorithm to improve the backdrivability performance of minimally invasive surgical robotic arms, so that precise manual manipulations of robotic arms can be performed in the preoperative operation.

Design/methodology/approach

First, the flexible-joint dynamic model of the 3-degree of freedom remote center motion (RCM) mechanisms of minimally invasive surgery (MIS) robot is derived and its dynamic parameters and friction parameters are identified. Next, the angular velocities and angular accelerations of joints are estimated in real time by the designed Kalman filter. Finally, a control algorithm based on Kalman filter is proposed to enhance the backdrivability of RCM mechanisms by compensating for the internally generated gravitational, frictional and inertial resistances experienced during the positioning and orientating.

Findings

The parameter identification for RCM mechanisms can be experimentally evaluated from comparison between the measured torques and the reconstructed torques. The accuracy and convergence of the real-time estimation of angular velocity and acceleration of the joint by the designed Kalman filter can be verified from corresponding simulation experiments. Manual adjustment experiments and animal experiments validate the effectiveness of the proposed backdrivability control algorithm.

Research limitations/implications

The backdrivability control algorithm presented in this paper is a universal method to enhance the manual operation performance of robots, which can be used not only in the medical robot preoperative manual manipulation but also in robot haptic interaction, industrial robot direct teaching and active rehabilitation training of rehabilitation robot and so on.

Originality/value

Compared with other backdrivability design methods, the proposed algorithm achieves good backdrivability for RCM mechanisms without using force sensors and accelerometers. In addition, this paper presents a new static friction compensation approach for a joint moving with very low velocity.

Details

Industrial Robot: An International Journal, vol. 45 no. 1
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 15 May 2017

Yue Ai, Bo Pan, Yili Fu and Shuguo Wang

Robot-assisted system for minimally invasive surgery (MIS) has been attracting more and more attentions. Compared with a traditional MIS, the robot-assisted system for MIS…

Abstract

Purpose

Robot-assisted system for minimally invasive surgery (MIS) has been attracting more and more attentions. Compared with a traditional MIS, the robot-assisted system for MIS is able to overcome or reduce defects, such as poor hand-eye coordination, heavy labour intensity and limited motion of the instrument. The purpose of this paper is to design a novel robotic system for MIS applications.

Design/methodology/approach

A robotic system with three separate slave arms for MIS has been designed. In the proposed robot, a new mechanism was designed as the remote centre motion (RCM) mechanism to restrain the movement of instrument or laparoscope around the incision. Moreover, an improved instrument without coupling motion between wrist and grippers was developed to enhance its manipulability. A control system architecture was also developed, and an intuitive control method was applied to realize hand-eye coordination of the operator.

Findings

For the RCM mechanism, the workspace was analyzed and the positioning accuracy of the remote centre point was tested. The results show that the RCM mechanism can be applied to MIS. Furthermore, the master-slave trajectory tracking experiments reveal that slave robots are able to follow the movement of the master manipulators well. Finally, the feasibility of the robot-assisted system for MIS is proved by performing animal experiments successfully.

Originality/value

This paper offers a novel robotic system for MIS. It can accomplish the anticipated results.

Details

Industrial Robot: An International Journal, vol. 44 no. 3
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 29 April 2019

Guozhi Li, Fuhai Zhang, Yili Fu and Shuguo Wang

The purpose of this paper is to propose an error model for serial robot kinematic calibration based on dual quaternions.

Abstract

Purpose

The purpose of this paper is to propose an error model for serial robot kinematic calibration based on dual quaternions.

Design/methodology/approach

The dual quaternions are the combination of dual-number theory and quaternion algebra, which means that they can represent spatial transformation. The dual quaternions can represent the screw displacement in a compact and efficient way, so that they are used for the kinematic analysis of serial robot. The error model proposed in this paper is derived from the forward kinematic equations via using dual quaternion algebra. The full pose measurements are considered to apply the error model to the serial robot by using Leica Geosystems Absolute Tracker (AT960) and tracker machine control (T-MAC) probe.

Findings

Two kinematic-parameter identification algorithms are derived from the proposed error model based on dual quaternions, and they can be used for serial robot calibration. The error model uses Denavit–Hartenberg (DH) notation in the kinematic analysis, so that it gives the intuitive geometrical meaning of the kinematic parameters. The absolute tracker system can measure the position and orientation of the end-effector (EE) simultaneously via using T-MAC.

Originality/value

The error model formulated by dual quaternion algebra contains all the basic geometrical parameters of serial robot during the kinematic calibration process. The vector of dual quaternion error can be used as an indicator to represent the trend of error change of robot’s EE between the nominal value and the actual value. The accuracy of the EE is improved after nearly 20 measurements in the experiment conduct on robot SDA5F. The simulation and experiment verify the effectiveness of the error model and the calibration algorithms.

Details

Industrial Robot: the international journal of robotics research and application, vol. 46 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

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