Intelligent Robots

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Review of Power-Assisted Lower Limb Exoskeleton Robot

HE Guisong (贺贵松), HUANG Xuegong (黄学功), LI Feng (李峰), WANG Huixing (汪辉兴)

J Shanghai Jiaotong Univ Sci 2024, 29 (1): 1-15. DOI: 10.1007/s12204-022-2489-3

Abstract （676）

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Power-assisted lower limb exoskeleton robot is a wearable intelligent robot system involving mechanics,materials, electronics, control, robotics, and many other fields. The system can use external energy to provide additional power to humans, enhance the function of the human body, and help the wearer to bear weight that is previously unbearable. At the same time, employing reasonable structure design and passive energy storage can also assist in specific actions. First, this paper introduces the research status of power-assisted lower limb exoskeleton robots at home and abroad, and analyzes several typical prototypes in detail. Then, the key technologies such as structure design, driving mode, sensing technology, control method, energy management, and human-machine coupling are summarized, and some common design methods of the exoskeleton robot are summarized and compared. Finally, the existing problems and possible solutions in the research of power-assisted lower limb exoskeleton robots are summarized, and the prospect of future development trend has been analyzed.

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Review of Key Technologies for Developing Personalized Lower Limb Rehabilitative Exoskeleton Robots

TAO Jing, (陶璟), ZHOU Zhenhuan (周振欢)

J Shanghai Jiaotong Univ Sci 2024, 29 (1): 16-28. DOI: 10.1007/s12204-022-2452-3

Abstract （644）

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Rehabilitative training and assistance to daily living activities play critical roles in improving the life quality of lower limb dyskinesia patients and older people with motor function degeneration. Lower limb rehabilitative exoskeleton has a promising application prospect in support of the above population. In this paper, critical technologies for developing lower limb rehabilitative exoskeleton for individualized user needs are identi- fied and reviewed, including exoskeleton hardware modularization, bionic compliant driving, individualized gait planning and individual-oriented motion intention recognition. Inspired by the idea of servitization, potentials in exoskeleton product-service system design and its enabling technologies are then discussed. It is suggested that future research will focus on exoskeleton technology and exoskeleton-based service development oriented to an individual’s physical features and personalized requirements to realize better human-exoskeleton coordination in terms of technology, as well as accessible and high-quality rehabilitation and living assistance in terms of utility.

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Integrated Hydraulic-Driven Wearable Robot for Knee Assistance

ZHAO Yafei (赵亚飞), HUANG Chaoyi (黄超逸), ZOU Yuging(邹玉莹), ZOUKehan(邹可涵), zoU Xiaogang(邹笑阳), XUE .Jiaqi(薛嘉琦), LI Xiaoting(李晓婷), KOH Keng Huat, WANG Xiaojun(王小军), LAI Wai Chiu King(赖伟超), HU Yong(胡勇), XI Ning(席宁), WANG Zheng(王峥)

J Shanghai Jiaotong Univ Sci 2023, 28 (3): 289-295. DOI: 10.1007/s12204-023-2602-2

Abstract （425）

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Age-related diseases can lead to knee joint misfunction, making knee assistance necessary through the use of robotic wearable braces. However, existing wearable robots face challenges in force transmission and human motion adaptation, particularly among the elderly. Although soft actuators have been used in wearable robots, achieving rapid response and motion control while maintaining portability remains challenging. To address these issues, we propose a soft-robotic knee brace system integrated with multiple sensors and a direct-drive hydraulic actuation system. This approach allows for controlled and rapid force output on the portable hydraulic system. The multi-sensor feedback structure enables the robotic system to collaborate with the human body through human physiological signal and body motion information. The human user tests demonstrate that the knee robot provides assistive torques to the knee joint by being triggered by the electromyography signal and under human motion control.

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Progress in Force-Sensing Techniques for Surgical Robots

GAO Hongyan1, 2(高红岩), AI Xiaojie1, 2(艾孝杰), SUN Zhenglong3(孙正隆), CHEN Weidong1, 2(陈卫东), GAO Anzhu1, 2(高安柱)

J Shanghai Jiaotong Univ Sci 2023, 28 (3): 370-381. DOI: 10.1007/s12204-023-2607-x

Abstract （597）

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Force sensing is vital for situational awareness and safe interaction during minimally invasive surgery. Consequently, surgical robots with integrated force-sensing techniques ensure precise and safe operations. Over the past few decades, there has been considerable progress in force-sensing techniques for surgical robots. This review summarizes the existing electrically- and optically-based force sensors for surgical robots, including piezoresistive, piezoelectric, capacitive, intensity/phase-modulated, and fiber Bragg gratings. Their principles, applications, advantages, and limitations are also discussed. Finally, we summarize our conclusions regarding state-of-the-art force-sensing technologies for surgical robotics.

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Cable-Driven Flexible Exoskeleton Robot for Abnormal Gait Rehabilitation

XU Ziwei (徐子薇), XIE Le (谢叻)

J Shanghai Jiaotong Univ Sci 2022, 27 (2): 231-239. DOI: 10.1007/s12204-021-2403-4

Abstract （224）

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The number of people with abnormal gait in China has been increasing for years. Compared with traditional methods, lower limb rehabilitation robots which address problems such as longstanding human guidance may cause fatigue, and the training is lacking scientific and intuitive monitoring data. However, typical rigid rehabilitation robots are always meeting drawbacks like the enormous weight, the limitation of joint movement,and low comfort. The purpose of this research is to design a cable-driven flexible exoskeleton robot to assist in rehabilitation training of patients who have abnormal gait due to low-level hemiplegia or senility. The system consists of a PC terminal, a Raspberry Pi, and the actuator structure. Monitoring and training are realized through remote operation and interactive interface simultaneously. We designed an integrated and miniaturized driving control box. Inside the box, two driving cables on customized pulley-blocks with different radii can retract/release by one motor after transmitting the target position to the Raspberry Pi from the PC. The force could be transferred to the flexible suit to aid hip flexion and ankle plantar flexion. Furthermore, the passive elastic structure was intended to assist ankle dorsiflexion. We also adopted the predictable admittance controller,which uses the Prophet algorithm to predict the changes in the next five gait cycles from the current ankle angular velocity and obtain the ideal force curve through a functional relationship. The admittance controller can realize the desired force following. Finally, we finished the performance test and the human-subject experiment.Experimental data indicate that the exoskeleton can meet the basic demand of multi-joint assistance and improve abnormal postures. Meanwhile, it can increase the range of joint rotation and eliminate asymmetrical during walking.

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Eye Robotic System for Vitreoretinal Surgery

DAI Qianlin (代倩琳), XU Mengqiao (徐梦乔), SUN Xiaodong (孙晓东), XIE Le∗ (谢叻)

J Shanghai Jiaotong Univ Sci 2022, 27 (1): 1-6. DOI: 10.1007/s12204-021-2369-2

Abstract （569）

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Micro incision vitrectomy system (MIVS) is considered to be one of the most difficult tasks of eye surgery, due to its requirements of high accuracy and delicate operation under blurred vision environment. Therefore, robot-assisted ophthalmic surgery is a potential and efficient solution. Based on that consideration, a novel master-slave system for vitreoretinal surgery is realized. A 4-DOF remote center of motion (RCM) mechanism with a novel linear stage and end-effector is designed and the master-slave control system is implemented. The forward and inverse kinematics are analyzed for the controller implementation. Then, algorithms with motion scaling are also integrated into the control architecture for the purpose to enhance the surgeon’s operation accuracy. Finally, experiments on an eye model are conducted. The results show that the eye robotic system can fulfill surgeon’s motion following and simulate operation of vitrectomy, demonstrating the feasibility of this system.

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Novel Concentric Tube Robot Based on Double-Threaded Helical Gear Tube

CHEN Weichi(陈韦池), LIU Haocheng(刘浩城), LI Zijian(李子建), GUO Jing, (郭靖), ZHAI Zhenkun(翟振坤), MENG Wei(孟伟)

J Shanghai Jiaotong Univ Sci 2023, 28 (3): 296-306. DOI: 10.1007/s12204-023-2595-x

Abstract （311）

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Nasopharyngeal carcinoma is a malignant tumor originating from the nasal mucosa. It is a malignant tumor of the head and neck. Concentric tube robot (CTR), as it can form a complicated shape and access hardto-reach lesions, is often used in minimally invasive surgeries. However, some CTRs are bulky because of their transmission design. In this paper, a light CTR based on double-threaded helical gear tube is proposed. Such a CTR is less cumbersome than the traditional CTR as its actuation unit is compact and miniaturized. The mapping relationship between the gear tube attitude and motor output angle is obtained by kinematic analysis. The precision, stability, and repeatability of the driving mechanism are tested. The experimental results show that the positioning error in the translation test is less than 0.3 mm, the rolling angle error in the stability test is less than 0.6?, and the error in the translation repeatability test is less than 0.005 mm. Finally, a tip-targeting test is performed using the new CTR, which verifies the feasibility of the CTR for surgeries.

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Enhancement of Pinching Grasping Robustness Using a Multi-Structure Soft Gripper

LI Linlin (李林霖), GAO Feiyang (高飞扬), ZHENG Xiongfei(郑雄飞), ZHANG Liming(张黎明), LI Shijie (李世杰), WANG Heran(王赫然)

J Shanghai Jiaotong Univ Sci 2023, 28 (3): 307-311. DOI: 10.1007/s12204-022-2508-4

Abstract （233）

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Recently, soft grippers have garnered considerable interest in various fields, such as medical rehabilitation, due to their high compliance. However, the traditional PneuNet only reliably grasps medium and large objects via enveloping grasping (EG), and cannot realize pinching grasping (PG) to stably grasp small and thin objects as EG requires a large bending angle whereas PG requires a much smaller one. Therefore, we proposed a multi-structure soft gripper (MSSG) with only one vent per finger which combines the PneuNet in the proximal segment with the normal soft pneumatic actuator (NSPA) in the distal segment, allowing PG to be realized without a loss in EG and enhancing the robustness of PG due to the height difference between the distal and proximal segments. Grasping was characterized on the basis of the stability (finger bending angle describes) and robustness (pull-out force describes), and the bending angle and pull-out force of MSSG were analyzed using the finite element method. Furthermore, the grasping performance was validated using experiments, and the results demonstrated that the MSSG with one vent per finger was able to realize PG without a loss in EG and effectively enhance the PG robustness.

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Shape Sensing for Single-Port Continuum Surgical Robot Using Few Multicore Fiber Bragg Grating Sensors

LI Dingjia1,2,3,4(黎定佳)，WANG Chongang1,2,3(王重阳)，GUO Wei5(郭伟)，WANG Zhidong6(王志东)，ZHANG Zhongtao5(张忠涛)，LIU Hao1,2,3*(刘浩)

J Shanghai Jiaotong Univ Sci 2023, 28 (3): 312-322. DOI: 10.1007/s12204-023-2579-x

Abstract （302）

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We proposed a method for shape sensing using a few multicore fiber Bragg grating (FBG) sensors in a single-port continuum surgical robot (CSR). The traditional method of utilizing a forward kinematic model to calculate the shape of a single-port CSR is limited by the accuracy of the model. If FBG sensors are used for shape sensing, their accuracy will be affected by their number, especially in long and flexible CSRs. A fusion method based on an extended Kalman filter (EKF) was proposed to solve this problem. Shape reconstruction was performed using the CSR forward kinematic model and FBG sensors, and the two results were fused using an EKF. The CSR reconstruction method adopted the incremental form of the forward kinematic model, while the FBG sensor method adopted the discrete arc-segment assumption method. The fusion method can eliminate the inaccuracy of the kinematic model and obtain more accurate shape reconstruction results using only a small number of FBG sensors. We validated our algorithm through experiments on multiple bending shapes under different load conditions. The results show that our method significantly outperformed the traditional methods in terms of robustness and effectiveness.

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Visual Positioning of Nasal Swab Robot Based on Hierarchical Decision

LI Guozhia a(李国志)，ZOU Shuizhong b*(邹水中),DING Shuacue a(丁数学)

J Shanghai Jiaotong Univ Sci 2023, 28 (3): 323-329. DOI: 10.1007/s12204-023-2581-3

Abstract （249）

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This study focuses on a robot vision localization method for coping with the operational task of automatic nasal swab sampling. The application is important in the detection and epidemic prevention of Corona Virus Disease 2019 (COVID-19) to alleviate the large-scale negative impact of individuals suffering from pneumonia owing to COVID-19. In this method, the idea of a hierarchical decision network is used to consider the strong infectious characteristics of the COVID-19, which is followed by processing the robot behavior constraint condition. The visual navigation and positioning method using a single-arm robot for sampling is also planned, which considers the operation characteristics of medical staff. In the decision network, the risk factor for potential contact infection caused by swab sampling operations is established to avoid the spread among personnel. A robot visual servo control with artificial intelligence characteristics is developed to achieve a stable and safe nasal swab sampling operation. Experiments demonstrate that the proposed method can achieve good vision positioning for the robots and provide technical support for managing new major public health situations.

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Real-Time Slice-to-Volume Registration-Based Autonomous Navigation for Robot-Assisted Thyroid Biopsy

LI Jian1 (李坚)，WANG Xingchao1 (王星超)，ZHONG Min2 (钟敏)，ZHENG Jian2(郑剑)，SUN Zhenglong1*(孙正隆)

J Shanghai Jiaotong Univ Sci 2023, 28 (3): 330-338. DOI: 10.1007/s12204-023-2606-y

Abstract （202）

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With advancements in medical imaging and robotic technology, the idea of fully autonomous diagnosis and treatment has become appealing, from ethereal to tangible. Owing to its characteristics of non-invasiveness, non-radiation, and fast imaging speed, ultrasonography has been increasingly used in clinical practice, such as in obstetrics, gynecology, and surgical puncture. In this paper, we propose a real-time image-based visual servo control scheme using a hybrid slice-to-volume registration method. In this manner, the robot can autonomously locate the ultrasound probe to the desired posture according to preoperational planning, even in the presence of disturbances. The experiments are designed and conducted using a thyroid biopsy phantom model. The results show that the proposed scheme can achieve a refresh rate of up to 30 Hz and a tracking accuracy of (0.52±0.65) mm.

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On Flexible Trajectory Description for Effective Rigid Body Motion Reproduction and Recognition

YANG Jian xin(杨健鑫)，GUo Yao*(郭遥)

J Shanghai Jiaotong Univ Sci 2023, 28 (3): 339-347. DOI: 10.1007/s12204-023-2604-0

Abstract （163）

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Recognizing and reproducing spatiotemporal motions are necessary when analyzing behaviors and movements during human-robot interaction. Rigid body motion trajectories are proven as compact and informative clues in characterizing motions. A flexible dual square-root function (DSRF) descriptor for representing rigid body motion trajectories, which can offer robustness in the description over raw data, was proposed in our previous study. However, this study focuses on exploring the application of the DSRF descriptor for effective backward motion reproduction and motion recognition. Specifically, two DSRF-based reproduction methods are initially proposed, including the recursive reconstruction and online optimization. New trajectories with novel situations and contextual information can be reproduced from a single demonstration while preserving the similarities with the original demonstration. Furthermore, motion recognition based on DSRF descriptor can be achieved by employing a template matching method. Finally, the experimental results demonstrate the effectiveness of the proposed method for rigid body motion reproduction and recognition.

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Input-Constrained Hybrid Control of a Hyper-Redundant Mobile Medical Manipulator

ZHANG Kaibo1(张凯波)，CHEN Li1*(陈丽)，DONG Qi2(董琦)

J Shanghai Jiaotong Univ Sci 2023, 28 (3): 348-359. DOI: 10.1007/s12204-023-2580-4

Abstract （237）

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To reduce the risk of infection in medical personnel working in infectious-disease areas, we proposed a hyper-redundant mobile medical manipulator (HRMMM) to perform contact tasks in place of healthcare workers. A kinematics-based tracking algorithm was designed to obtain highly accurate pose tracking. A kinematic model of the HRMMM was established and its global Jacobian matrix was deduced. An expression of the tracking error based on the Rodrigues rotation formula was designed, and the relationship between tracking errors and gripper velocities was derived to ensure accurate object tracking. Considering the input constraints of the physical system, a joint-constraint model of the HRMMM was established, and the variable-substitution method was used to transform asymmetric constraints to symmetric constraints. All constraints were normalized by dividing by their maximum values. A hybrid controller based on pseudo-inverse (PI) and quadratic programming (QP) was designed to satisfy the real-time motion-control requirements in medical events. The PI method was used when there was no input saturation, and the QP method was used when saturation occurred. A quadratic performance index was designed to ensure smooth switching between PI and QP. The simulation results showed that the HRMMM could approach the target pose with a smooth motion trajectory, while meeting different types of input constraints.

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Foreground Segmentation Network with Enhanced Attention

JIANG Rui1*(姜﹐锐)，ZHU Ruiriang1(朱瑞祥)，CAI Xiaocui1(蔡萧萃)，SU Hu2(苏虎)

J Shanghai Jiaotong Univ Sci 2023, 28 (3): 360-369. DOI: 10.1007/s12204-023-2603-1

Abstract （332）

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Moving object segmentation (MOS) is one of the essential functions of the vision system of all robots,including medical robots. Deep learning-based MOS methods, especially deep end-to-end MOS methods, are actively investigated in this field. Foreground segmentation networks (FgSegNets) are representative deep end-to-end MOS methods proposed recently. This study explores a new mechanism to improve the spatial feature learning capability of FgSegNets with relatively few brought parameters. Specifically, we propose an enhanced attention (EA) module, a parallel connection of an attention module and a lightweight enhancement module, with sequential attention and residual attention as special cases. We also propose integrating EA with FgSegNet v2 by taking the lightweight convolutional block attention module as the attention module and plugging EA module after the two Maxpooling layers of the encoder. The derived new model is named FgSegNet v2 EA. The ablation study verifies the effectiveness of the proposed EA module and integration strategy. The results on the CDnet2014 dataset, which depicts human activities and vehicles captured in different scenes, show that FgSegNet v2 EA outperforms FgSegNet v2 by 0.08% and 14.5% under the settings of scene dependent evaluation and scene independent evaluation, respectively, which indicates the positive effect of EA on improving spatial feature learning capability of FgSegNet v2.

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Development of Rehabilitation and Assistive Robots in China: Dilemmas and Solutions

ZHAO Lingling1*(赵玲玲),GUO Yao2(郭遥)

J Shanghai Jiaotong Univ Sci 2023, 28 (3): 382-390. DOI: 10.1007/s12204-023-2596-9

Abstract （317）

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China is rapidly becoming an aging society, leading to a significant demand for chronic disease management and personalized healthcare. The development of rehabilitation and assistive robotics in China has gathered significant attention not only in research fields but also in industries. Such robots aim to either guide patients in completing therapeutic training or assist people with impaired functions in performing their daily activities. In the past decades, we have witnessed the advancement in rehabilitation and assistive robotics, with diverse mechanical designs, functionalities, and purposes. However, the construction of dedicated regulations and policies is relatively lagged compared with the flourishing development in research fields. Moreover, these kinds of robots are working or collaborating closely with human beings, bringing unprecedented considerations on ethical issues. This paper aims to provide an overview of major dilemmas in the development of rehabilitation and assistive robotics in China and propose several potential solutions.

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Hysteresis Modeling and Compensation for Distal Shaft Deflection of Flexible Ureteroscope

HUA Penga (华鹏)， SHU Xiongpenga (舒雄鹏)，XIE Lea,b* (谢叻)

J Shanghai Jiaotong Univ Sci 2023, 28 (4): 507-. DOI: 10.1007/s12204-022-2505-7

Abstract （125）

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Flexible ureteroscopy (FURS) has been widely used in the diagnosis and treatment of upper urinarytract diseases. The key operation of FURS is that the surgeon manipulates the distal shaft of flexible ureteroscopeto a specific target for diagnosis and treatment. However, the hysteresis of flexible ureteroscope may be one ofthe most important factors that degrade the manipulation accuracy and the surgeon usually spends a long timenavigating the distal shaft during surgery. In this study, we obtained hysteresis curves of distal shaft deflectionfor the flexible ureteroscope through extensive repeated experiments. Then, two methods based on piecewiselinear approximation and long short-term memory neural network were employed to model the hysteresis curves.On this basis, we proposed two hysteresis compensation strategies for the distal shaft deflection. Finally, wecarried out hysteresis compensation experiments to verify the two proposed compensation strategies. Experimentalresults showed that the hysteresis compensation strategies can significantly improve position accuracy with meancompensation errors of no more than 5?.

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A Novel Cable-Driven Soft Robot for Surgery

LI Ru1 (李茹), CHEN Fang2 (陈方), YU Wenwei3 (俞文伟), IGARASH Tatsuo3,4, SHU Xiongpeng1 (舒雄鹏), XIE Le1,5,6∗ (谢叻)

J Shanghai Jiaotong Univ Sci 2024, 29 (1): 60-72. DOI: 10.1007/s12204-022-2497-3

Abstract （129）

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Robot-assisted laparoscopic radical prostatectomy (RARP) is widely used to treat prostate cancer. The rigid instruments primarily used in RARP cannot overcome the problem of blind areas in surgery and lead to more trauma such as more incision for the passage of the instrument and additional tissue damage caused by rigid instruments. Soft robots are relatively flexible and theoretically have infinite degrees of freedom which can overcome the problem of the rigid instrument. A soft robot system for single-port transvesical robot-assisted radical prostatectomy (STvRARP) is developed in this study. The soft manipulator with 10 mm in diameter and a maximum bending angle of 270? has good flexibility and dexterity. The design and mechanical structure of the soft robot are described. The kinematics of the soft manipulator is established and the inverse kinematics is compensated based on the characteristics of the designed soft manipulator. The master-slave control system of soft robot for surgery is built and the feasibility of the designed soft robot is verified.

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Multi-Robot Task Allocation Using Multimodal Multi-Objective Evolutionary Algorithm Based on Deep Reinforcement Learning

MIAO Zhenhua(苗镇华), HUANG Wentao(黄文焘), ZHANG Yilian(张依恋), FAN Qinqin(范勤勤)

J Shanghai Jiaotong Univ Sci 2024, 29 (3): 377-387. DOI: 10.1007/s12204-023-2679-7

Abstract （354）

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The overall performance of multi-robot collaborative systems is significantly affected by the multirobot task allocation. To improve the effectiveness, robustness, and safety of multi-robot collaborative systems,a multimodal multi-objective evolutionary algorithm based on deep reinforcement learning is proposed in this paper. The improved multimodal multi-objective evolutionary algorithm is used to solve multi-robot task allocation problems. Moreover, a deep reinforcement learning strategy is used in the last generation to provide a high-quality path for each assigned robot via an end-to-end manner. Comparisons with three popular multimodal multi-objective evolutionary algorithms on three different scenarios of multi-robot task allocation problems are carried out to verify the performance of the proposed algorithm. The experimental test results show that the proposed algorithm can generate sufficient equivalent schemes to improve the availability and robustness of multirobot collaborative systems in uncertain environments, and also produce the best scheme to improve the overall task execution efficiency of multi-robot collaborative systems.

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Fast Four-Stage Local Motion Planning Method for Mobile Robot

HUANG Shan(黄山), HUANG Hongzhong(黄洪钟), ZENG Qi(曾奇)

J Shanghai Jiaotong Univ Sci 2024, 29 (3): 428-435. DOI: 10.1007/s12204-022-2423-8

Abstract （72）

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Mobile robot local motion planning is responsible for the fast and smooth obstacle avoidance, which is one of the main indicators for evaluating mobile robots’ navigation capabilities. Current methods formulate local motion planning as a unified problem; therefore it cannot satisfy the real-time requirement on the platform with limited computing ability. In order to solve this problem, this paper proposes a fast local motion planning method that can reach a planning frequency of 500 Hz on a low-cost CPU. The proposed method decouples the local motion planning as the front-end path searching and the back-end optimization. The front-end is composed of the environment topology analysis and graph searching. The back-end includes dynamically feasible trajectory generation and optimal trajectory selection. Different from the popular methods, the proposed method decomposes the local motion planning into four sub-modules, each of which aims to solve one problem. Combining four submodules, the proposed method can obtain the complete local motion planning algorithm which can fast generate a smooth and collision-free trajectory. The experimental results demonstrate that the proposed method has the ability to obtain the smooth, dynamically feasible and collision-free trajectory and the speed of the planning is fast.

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Establishment of Constraint Relation of Robot Dynamics Equation Based on Kinematic Influence Coefficients Method

XU Yaru(徐亚茹), LI Kehong(李克鸿), SHANG Xinna（商新娜）, JIN Xiaoming(金晓明), LIU Rong(刘荣), ZHANG Jiancheng（张建成）

J Shanghai Jiaotong Univ Sci 2024, 29 (3): 450-456. DOI: 10.1007/s12204-023-2661-4

Abstract （40）

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Due to the diversity of work requirements and environment, the number of degrees of freedom (DOFs) and the complexity of structure of industrial robots are constantly increasing. It is difficult to establish the accurate dynamical model of industrial robots, which greatly hinders the realization of a stable, fast and accurate trajectory tracking control. Therefore, the general expression of the constraint relation in the explicit dynamic equation of the multi-DOF industrial robot is derived on the basis of solving the Jacobian matrix and Hessian matrix by using the kinematic influence coefficients method. Moreover, an explicit dynamic equation with general constraint relation expression is established based on the Udwadia-Kalaba theory. The problem of increasing the time of establishing constraint relationship when the multi-DOF industrial robots complete complex task constraints is solved. With the SCARA robot as the research object, the simulation results show that the proposed method can provide a new idea for industrial robot system modeling with complex constraints.

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Multi-Agent Path Planning Method Based on Improved Deep Q-Network in Dynamic Environments

LI Shuyi (李舒逸), LI Minzhe (李旻哲), JING Zhongliang^∗ (敬忠良)

J Shanghai Jiaotong Univ Sci 2024, 29 (4): 601-612. DOI: 10.1007/s12204-024-2732-1

Abstract （215）

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The multi-agent path planning problem presents significant challenges in dynamic environments, primarily due to the ever-changing positions of obstacles and the complex interactions between agents’ actions. These factors contribute to a tendency for the solution to converge slowly, and in some cases, diverge altogether. In addressing this issue, this paper introduces a novel approach utilizing a double dueling deep Q-network (D3QN), tailored for dynamic multi-agent environments. A novel reward function based on multi-agent positional constraints is designed, and a training strategy based on incremental learning is performed to achieve collaborative path planning of multiple agents. Moreover, the greedy and Boltzmann probability selection policy is introduced for action selection and avoiding convergence to local extremum. To match radar and image sensors, a convolutional neural network - long short-term memory (CNN-LSTM) architecture is constructed to extract the feature of multi-source measurement as the input of the D3QN. The algorithm’s efficacy and reliability are validated in a simulated environment, utilizing robot operating system and Gazebo. The simulation results show that the proposed algorithm provides a real-time solution for path planning tasks in dynamic scenarios. In terms of the average success rate and accuracy, the proposed method is superior to other deep learning algorithms, and the convergence speed is also improved.

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CBF-Based Distributed Model Predictive Control for Safe Formation of Autonomous Mobile Robots

MU Jianbin^∗ (穆建彬), YANG Haili (杨海丽), HE Defeng (何德峰)

J Shanghai Jiaotong Univ Sci 2024, 29 (4): 678-688. DOI: 10.1007/s12204-024-2747-7

Abstract （47）

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A distributed model predictive control (DMPC) method based on robust control barrier function (RCBF) is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed environment. The first step is to analyze the safety requirements of the system during safe formation and categorize them into collision avoidance and distance connectivitymaintenance. RCBF constraints are designed based on collision avoidance and connectivity maintenance requirements, and security constraints are achieved through a combination. Then, the specified safety constraints are integrated with the objective of forming a multi-autonomous mobile robot formation. To ensure safe control, the optimization problem is integrated with the DMPC method. Finally, the RCBF-DMPC algorithm is proposed to ensure iterative feasibility and stability while meeting the constraints and expected objectives. Simulation experiments illustrate that the designed algorithm can achieve cooperative formation and ensure system security.

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