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Transportation Safety and Environment 2024年第2期6卷 24-35页

作者： Jiahao Huang Steffen Jung inger Hui Liu Kerstin Thurow Center for Life Science Automation(CELISCA) University of RostockRostock 18119Germany Institute of Automation University of RostockRostock 18119Germany Institute of Artificial Intelligence&Robotics(IAIR) School of Traffic&Transportation EngineeringCentral South UniversityChangsha 410075HunanChina

The increasing use of mobile robots in laboratory settings has led to a higher degree of laboratory automation.However,when mobile robots move in laboratory environments,mechanical errors,environmental disturbances and signal interruptions are inevitable.This can compromise the accuracy of the robot’s localization,which is crucial for the safety of staff,robots and the laboratory.A novel time-series predicting model based on the data processing method is proposed to handle the unexpected localization measurement of mobile robots in laboratory environments.The proposed model serves as an auxiliary localization system that can accurately correct unexpected localization errors by relying solely on the historical data of mobile robots.The experimental results demonstrate the effectiveness of this proposed method.

关键词： mobile robots laboratory automation indoor localization neural network

Target Tracking Algorithm Using Finite-time Convergence Smooth Second-order Sliding Mode Controller for mobile robots

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Chinese Journal of Mechanical Engineering 2011年第3期24卷 414-419页

作者： GE Lianzheng ZHAO Lijun GAO Tong State Key Laboratory of Robotics Technique and System Harbin Institute of Technology Harbin 150001 China

Target tracking control for wheeled mobile robot （WMR） need resolve the problems of kinematics model and tracking algorithm.High-order sliding mode control is a valid method used in the nonlinear tracking control system,which can eliminate the chattering of sliding mode control.Currently there lacks the research of robustness and uncertain factors for high-order sliding mode control.To address the fast convergence and robustness problems of tracking target,the tracking mathematical model of WMR and the target is derived.Based on the finite-time convergence theory and second order sliding mode method,a nonlinear tracking algorithm is designed which guarantees that WMR can catch the target in finite time.At the same time an observer is applied to substitute the uncertain acceleration of the target,then a smooth nonlinear tracking algorithm is proposed.Based on Lyapunov stability theory and finite-time convergence,a finite time convergent smooth second order sliding mode controller and a target tracking algorithm are designed by using second order sliding mode method.The simulation results verified that WMR can catch up the target quickly and reduce the control discontinuity of the velocity of WMR.

关键词： mobile robots second order sliding mode finite-time convergence observer

ALLIANCE-ROS:A Software Framework on ROS for Fault-Tolerant and Cooperative mobile robots

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Chinese Journal of Electronics 2018年第3期27卷 467-475页

作者： GUO Zhongyuan YANG Wenjing LI Minglong YI Xiaodong CAI Zhongxuan WANG Yanzhen State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology

Programming control systems for mobile robots is complicated and time-consuming, due to three aspects, i.e., the robot behavior coordination, the distributed multi-robot cooperation and the robot software reusability. Subsumption model is a robust control architecture for mobile robots. ALLIANCE model extends it to multirobot systems, which is a fully distributed, fault-tolerant model. Robot operating system(ROS) provides a lot of reusable robot modules. By combining the above three, we propose a software framework named ALLIANCE-ROS for developing fault-tolerant cooperative multi-robot systems with abundant software resources available. We encapsulate the ROS facilities to build the framework prototype.We also use some high-performance plugin-based mechanism to optimize the bottom of the framework. One may use the framework-provided API conveniently to construct single-robot and multi-robot applications with all ROS resources available. This work is demonstrated by three application cases including an autonomous roving robot, a security patrol robot and multiple patrol robots. They are constructed and tested in both the simulated and the real environment. The experimental results validate the usability and availability of ALLIANCE-ROS.

关键词： Software framework mobile robots Cooperative robots Fault-tolerance ALLIANCE-ROS

Deep reinforcement learning for shared control of mobile robots

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IET Cyber-Systems and Robotics 2021年第4期3卷 315-330页

作者： Chong Tian Shahil Shaik Yue Wang Mechanical Engineering Department Clemson UniversityClemsonSouth CarolinaUSA

Shared control of mobile robots integrates manual input with auxiliary autonomous controllers to improve the overall system performance.However,prior work that seeks to find the optimal shared control ratio needs an accurate human model,which is usually challenging to obtain.In this study,the authors develop an extended Twin Delayed Deep Deterministic Policy Gradient(DDPG)(TD3X)-based shared control framework that learns to assist a human operator in teleoperating mobile robots optimally.The robot's states,shared control ratio in the previous time step,and human's control input is used as inputs to the reinforcement learning(RL)agent,which then outputs the optimal shared control ratio between human input and autonomous controllers without knowing the human model.Noisy softmax policies are developed to make the TD3X algorithm feasible under the constraint of a shared control ratio.Furthermore,to accelerate the training process and protect the robot,a navigation demonstration policy and a safety guard are developed.A neural network(NN)structure is developed to maintain the correlation of sensor readings among heterogeneous input data and improve the learning speed.In addition,an extended DAGGER(DAGGERX)human agent is developed for training the RL agent to reduce human workload.Robot simulations and experiments with humans in the loop are conducted.The results show that the DAGGERX human agent can simulate real human inputs in the worst-case scenarios with a mean square error of 0.0039.Compared to the original TD3 agent,the TD3X-based shared control system decreased the average collision number from 387.3 to 44.4 in a simplistic environment and 394.2 to 171.2 in a more complex environment.The maximum average return increased from 1043 to 1187 with a faster converge speed in the simplistic environment,while the performance is equally good in the complex environment because of the use of an advanced human agent.In the human subject tests,participants'average perceived workload was significantly lower in shared control

关键词： control deep learning human robot interaction mobile robots reinforcement learning

Multi-floor laboratory transportation technologies based on intelligent mobile robots

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Transportation Safety and Environment 2019年第1期1卷 37-53页

作者： Kerstin Thurow Lei Zhang Hui Liu Steffen Junginger Norbert Stoll Jiahao Huang Center for Life Science Automation(CELISCA) University of RostockRostock 18119Germany Institute of Artificial Intelligence&Robotics(IAIR) Key Laboratory of Traffic Safety on Track of Ministry of EducationSchool of Traffic&Transportation EngineeringCentral South UniversityChangsha 410075HunanChina Institute of Automation University of RostockRostock 18119Germany

Transportation technologies for mobile robots include indoor navigation,intelligent collision avoidance and target manipulation.This paper discusses the research process and development of these interrelated technologies.An efficient multi-floor laboratory transportation system for mobile robots developed by the group at the Center for Life Science Automation(CELISCA)is then introduced.This system is integrated with the multi-floor navigation and intelligent collision avoidance systems,as well as a labware manipulation system.A multi-floor navigation technology is proposed,comprising sub-systems for mapping and localization,path planning,door control and elevator operation.Based on human-robot interaction technology,a collision avoidance system is proposed that improves the navigation of the robots and ensures the safety of the transportation process.Grasping and placing operation technologies using the dual arms of the robots are investigated and integrated into the multi-floor transportation system.The proposed transportation system is installed on the H20 mobile robots and tested at the CELISCA laboratory.The results show that the proposed system can ensure the mobile robots are successful when performing multi-floor laboratory transportation tasks.

关键词： robots mobile robots laboratory transportation navigation

An adaptive particle filter for soft fault compensation of mobile robots

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Science in China(Series F) 2008年第12期51卷 2033-2046页

作者： DUAN ZhuoHua CAI ZiXing YU JinXia School of Information Engineering Shaoguan University Shaoguan 512003 China School of Information Science and Engineering Central South University Changsha 410083 China College of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China

Soft fault compensation plays an important role in mobile robot locating, mapping, and navigating. It is difficult to achieve fast and accurate compensation for mobile robots because they are usually highly non-linear, non-Gaussian systems with limited computation and memory resources. An adaptive particle filter is presented to compensate two kinds of soft faults for mobile robots, i.e., noise or factor faults of dead reckoning sensors and slippage of wheels. Firstly, the kinematics models and the fault models are discussed, and five kinds of residual features are extracted to detect soft faults. Secondly, an adaptive particle filter is designed for fault compensation, and two kinds of adaptive scheme are discussed： 1） the noise variances of linear speed and yaw rate are adjusted according to residual features; 2） the particle number is adapted according to Kullback-Leibler divergence （KLD） of two approximate distribution denoted with two particle sets with different particles, i.e., increasing particle number if the KLD is large and decreasing particle number if the KLD is small. The theoretic proof is given and experimental results show the efficiency and accuracy of the presented approach.

关键词： soft fault detection and compensation adaptive particle filter mobile robots

Distributed Consensus of Multiple Nonholonomic mobile robots

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IEEE/CAA Journal of Automatica Sinica 2014年第2期1卷 162-170页

作者： Kecai Cao Bin Jiang Dong Yue College of Automation Nanjing University of Posts and Telecommunications College of Automation Engineering Nanjing University of Aeronautics and Astronautics

Consensus problems of multiple nonholonomic mobile robots are considered in this paper. These problems are simplified into consensus problems of two subsystems based on structure of nonholonomic mobile robots. Linear distributed controllers are constructed respectively for these two subsystems thanks to the theory of nonautonomous cascaded systems. Consensus of multiple nonholonomic mobile robots has been realized using the methodology proposed in this paper no matter whether the group reference signal is persistent excitation or not. Different from previous research on cooperative control of nonholonomic mobile robots where the consensus problem under persistent exciting reference has received a lot of attention, this paper reports the first consensus result for multiple nonholonomic mobile robots whose group reference converges to zero. Simulation results using Matlab illustrate the effectiveness of the proposed controllers in this paper.

关键词： mobile robots Protocols Topology Control systems Robot kinematics Time-varying systems

Accurate parameter estimation of systematic odometry errors for two-wheel differential mobile robots

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Journal of Measurement Science and Instrumentation 2012年第3期3卷 268-272页

作者： Changbae Jung Woojin Chung School of Mechanical Engineering Korea University

Odometry using incremental wheel encoder sensors provides the relative robot pose estimation.However,the odometry suffers from the accumulation of kinematic modeling errors of wheels as the robot's travel distance increases.Therefore,the systematic errors need to be calibrated.The University of Michigan Benchmark(UMBmark)method is a widely used calibration scheme of the systematic errors in two-wheel differential mobile robots.In this paper,the accurate parameter estimation of systematic errors is proposed by extending the conventional method.The contributions of this paper can be summarized as two issues.The first contribution is to present new calibration equations that reduce the systematic odometry errors.The new equations were derived to overcome the limitation of conventional schemes.The second contribution is to propose the design guideline of the test track for calibration experiments.The calibration performance can be improved by appropriate design of the test track.The simulations and experimental results show that the accurate parameter estimation can be implemented by the proposed method.

关键词： calibration kinematic modeling errors mobile robots odometry test tracks

Design and motion analysis of reconfigurable wheel-legged mobile robot

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Defence Technology（防务技术） 2022年第6期18卷 1023-1040页

作者： Shuo Zhang Jian-tao Yao Ying-bin Wang Zi-sheng Liu Yun-dou Xu Yong-sheng Zhao School of Mechanical Engineering Yanshan UniversityHebeiChina

An adaptive wheel-legged shape reconfigurable mobile robot,based on a scissor-like mechanism,is proposed for an obstacle detecting and surmounting robot,moving on complex terrain.The robot can dynamically adjust its own shape,according to the environment,realizing a transformation of wheel shape into leg shape and vice versa.Each wheel-legged mechanism has one degree of freedom,which means that only the relative motion of the inner and outer discs is needed to achieve the transformation of the shape into a wheel or a leg.First,the force analysis of the conversion process of the wheel-legged mechanism is carried out,while the relationship between the driving torque and the friction factor in the non-conversion trigger stage and in the conversion trigger stage is obtained.The results showed that the shape conversion can be better realized by increasing the friction factor of the trigger point.Next,the kinematics analysis of the robot,including climbing the obstacles,stairs and gully,is carried out.The motion of the spokes tip is obtained,in order to derive the folding ratio and the surmountable obstacle height of the wheel-legged mechanism.The parameters of the wheel-legged structure are optimized,to obtain better stability and obstacle climbing ability.Finally,a dynamic simulation model is established by ADAMS,to verify the obstacle climbing performance and gait rationality of the robot,in addition to a prototype experiment.The results showed that the surmountable obstacle height of the robot is about3.05 times the spoke radius.The robot has the stability of a traditional wheel mechanism and the obstacle surmount performance of a leg mechanism,making it more suitable for field reconnaissance and exploration missions.

关键词： mobile robots Scissor mechanism Kinematics ADAMS simulation Obstacle surmounting

Spherical robot: A novel robot for exploration in harsh unknown environments

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IET Cyber-Systems and Robotics 2023年第4期5卷 1-15页

作者： Wei Ren You Wang Haoxiang Liu Song Jin Yixu Wang Yifan Liu Ziang Zhang Tao Hu Guang Li State Key Laboratory of Industrial Control Technology Institute of Cyber Systems and ControlZhejiang UniversityHangzhouChina

The authors propose a complete software and hardware framework for a novel spherical robot to cope with exploration in harsh and unknown environments.The proposed robot is driven by a heavy pendulum covered by a fully enclosed spherical shell,which is strongly protected,amphibious,anti-overturn and has a long-battery-life.Algorithms for location and perception,planning and motion control are comprehensively designed.On the one hand,the authors fully consider the kinematic model of a spherical robot,propose a positioning algorithm that fuses data from inertial measurement units,motor encoder and Global Navigation Satellite System,improve global path planning algorithm based on Hybrid A*and design an instruction planning controller based on model predictive control(MPC).On the other hand,the dynamic model is built,linear MPC and robust servo linear quadratic regulator algorithm is improved,and a speed controller and a direction controller are designed.In addition,based on the pose and motion charac-teristics of a spherical robot,a visual obstacle perception algorithm and an electronic image stabilisation algorithm are designed.Finally,the authors build physical systems to verify the effectiveness of the above algorithms through experiments.

关键词： mobile robots robot control robot perception robot planning