Robotics and Autonomous Systems最新文献

{"title":"Design and motion analysis of a simple screw driven in-pipe inspection robot base on adaptive variable pitch","authors":"Jihua Yin ,&nbsp;Xuemei Liu,&nbsp;Maokun Rui,&nbsp;Miao Yu","doi":"10.1016/j.robot.2025.105148","DOIUrl":"10.1016/j.robot.2025.105148","url":null,"abstract":"<div><div>In-pipe inspection robot (IPIR) play an important role in detecting the quality of the inner walls of oil and gas transportation pipelines and urban pipelines. However, due to the complex structure of the pipeline, robot is required to have adaptability. The currently existing screw driven pipeline robot has a fixed pitch, and the robot passively and rigidly pass through pipeline curvature. This article designs a simple adaptive variable pitch pipeline robot. The robot is driven by an electric motor and has simple motion control. The robot consists of a rotor that can adapt to changes in pipeline diameter and a stator with fixed dimensions. The robot adapts through pipeline curvature by continuously adjusting the pitch. The robot is equipped with a wide-angle lens and transmits quality images of the inner wall of the pipeline through Wi-Fi. Through theoretical analysis and model experiments, the robot can smoothly pass through vertical pipes with a diameter of 160 mm and 90-degree pipeline curvature.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105148"},"PeriodicalIF":5.2,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144852074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trajectory tracking model predictive control for mobile robot based on deep Koopman operator modeling","authors":"Minan Tang ,&nbsp;Yaqi Zhang ,&nbsp;Shuyou Yu ,&nbsp;Jinping Li ,&nbsp;Kunxi Tang","doi":"10.1016/j.robot.2025.105152","DOIUrl":"10.1016/j.robot.2025.105152","url":null,"abstract":"<div><div>Trajectory tracking serves as a pivotal performance metric for mobile robot systems, and is crucial for improving the efficiency of robots. The intricate kinematic and dynamic properties of robot systems pose substantial challenges in achieving accurate modeling and effective control, which remain pressing issues within the current research domain. This study focuses on wheeled mobile robot, relying on the deep Koopman operator theory, combined with the extended state observer (ESO) and the adaptive predictive time domain self-triggered model predictive control (APST-MPC) method, to propose a data-driven solution for the trajectory tracking control issue of wheeled mobile robot under uncertain model parameters. Firstly, the dynamic model of the mobile robot is constructed by the deep Koopman operator method. Secondly, to counteract operational disturbances encountered by the robot, an ESO is designed for disturbance estimation and subsequent compensation within the controller. Thirdly, to reduce the computational load, APST-MPC is employed to enhance the trajectory tracking control of wheeled mobile robot. Ultimately, the efficacy of the proposed trajectory tracking controller is confirmed through simulation experiments. The simulation outcomes confirm the deep Koopman operator theory’s efficacy in establishing a robot model with considerable accuracy, the tracking error of the robot is reduced by 46.03% and the total number of triggering times of the system is reduced by more than 59.8% by the APST-MPC controller based on ESO compared with the MPC controller.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105152"},"PeriodicalIF":5.2,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Circulation-embedded Control Barrier Function for safe navigation: A solution to avoid undesired equilibria and dysfunctional circulation","authors":"Shaghayegh Keyumarsi,&nbsp;Made Widhi Surya Atman ,&nbsp;Azwirman Gusrialdi","doi":"10.1016/j.robot.2025.105132","DOIUrl":"10.1016/j.robot.2025.105132","url":null,"abstract":"<div><div>The Control Barrier Function (CBF) is widely adopted in safety-critical applications such as safe navigation in an unknown environment. CBF quadratic program (CBF-QP) is a conventional CBF framework that acts as a safety filter. However, CBF-QP is prone to deadlocks, especially in dynamic and multi-agent environments, although it also occurs with convex obstacles. Specifically, CBF-QP suffers from several challenges, including undesired equilibria, accompanying slowdown behavior around these points, dysfunctional circulation, and becoming trapped in the obstacle. In this paper, we propose a practical solution to address these issues. First, we introduce the foundational principles and parameters for the proposed circulation-embedded CBF algorithm, which incorporates an effective circulation linear inequality constraint into CBF-QP. Moreover, input bounds constraints are incorporated to ensure that the rectified input is readily applicable and optimal. Then, we study the feasibility, continuity, equilibrium points, and convergence of the proposed circulation-embedded CBF-QP algorithm through propositions and formal proofs. Finally, the effectiveness of the proposed algorithm is demonstrated through experiments and comparisons involving unknown nonconvex obstacles and multi-robot scenarios without communication. The source code is released for the reference of the community. <span><span>²</span></span></div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105132"},"PeriodicalIF":5.2,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144842861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analytical inverse kinematic solution for the redundant 7-DoF manipulator","authors":"Gang Wang ,&nbsp;Wenjun Li ,&nbsp;Xiaoshan Gao ,&nbsp;Qi Zhang","doi":"10.1016/j.robot.2025.105142","DOIUrl":"10.1016/j.robot.2025.105142","url":null,"abstract":"<div><div>This paper proposes a novel parameterization analytical method to solve the inverse kinematics of a redundant 7-DoF manipulator. The current arm-angle parameterization methods cannot describe the self-motion of the elbow joint well. To address this issue, a novel arm length parameter that describes the manipulator’s redundancy is defined to represent the self-motion manifold of the elbow motion. Then the analytical inverse kinematics solutions can be obtained by utilizing arm length parameter and global configuration parameters. The joint angle constraints and singularity constraints are mapped to the arm length parameter space, and the feasible arm length intervals are derived. Furthermore, a redundant parameter optimization method is proposed based on the hierarchical motion control strategy, which applies the feasible arm length interval into the redundancy resolution problem. Numerical simulations are conducted to verify the proposed inverse kinematics method can reduce motion amplitude of joint angles during trajectory tracking and thus improve the motion accuracy of the manipulator compared with the traditional methods.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105142"},"PeriodicalIF":5.2,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144809212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-based controller for a soft robot actuated by ultrasonic atomization with unknown dynamics and uncertainty","authors":"Josué Gómez ,&nbsp;Arturo Baltazar ,&nbsp;Isaias Campos ,&nbsp;Chidentree Treesatayapun","doi":"10.1016/j.robot.2025.105143","DOIUrl":"10.1016/j.robot.2025.105143","url":null,"abstract":"<div><div>Soft robots are increasingly indispensable in engineering and scientific applications due to their ability to navigate unstructured environments, interact with humans, and emulate biological systems. These tasks pose challenges for rigid robots. Traditional actuation methods for soft robots rely on pneumatic or hydraulic systems, which may face limitations in miniaturized soft robots. Here, a soft robot featuring an actuation system based on vibrating mesh atomization and ethanol evaporation is introduced. However, the physical process of this actuator introduces noise, non-linearity, and hysteresis during displacement and force cycles. Thus, the inherent uncertainty and lack of a dynamic model pose challenges for a classical model-based control. Existing data-based controllers typically prioritize minimizing cost functions to address this issue. In this study, a novel data-based fuzzy network controller for the discussed soft actuation is proposed, integrating an input error function within a sliding mode framework. The controller, along with its learning law, is specifically designed to tackle time-varying parameters resulting from the hysteresis and nonlinear characteristics of soft robots. Rigorous analysis is provided using the Lyapunov method to validate the proposed approach. Numerical experiments were performed using an approximate discretized nonlinear model with noise to describe the data reported in the literature. Experimental validation involves measuring the voltage of a micro-force sensor to track blocking force as a control signal to the plant. Both numerical and experimental results validate the efficacy of the proposed controller in force tracking under external perturbations.</div><div>Soft robots play an essential role in engineering and scientific applications due to their adaptability in unstructured environments, safe human interaction, and biomimetic capabilities—challenges that rigid robots face. Traditional actuation methods, such as pneumatic and hydraulic systems, exhibit limitations in miniaturized soft robots. This study presents a soft robot actuated by vibrating mesh atomization and ethanol evaporation. However, the actuator introduces noise, nonlinearity, and hysteresis, complicating model-based control. To address these challenges, a data-driven fuzzy network controller is proposed, integrating an input error function within a sliding mode framework. The controller and its learning law are designed to accommodate time-varying parameters associated with hysteresis and nonlinear behavior. Stability is rigorously analyzed using the Lyapunov method. Numerical experiments utilize a discretized nonlinear model with noise to approximate reported data. Experimental validation measures the voltage of a micro-force sensor to track blocking force as a control signal. Both numerical and experimental results confirm the controller’s effectiveness in force tracking under external perturbations.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105143"},"PeriodicalIF":5.2,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144842860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamics, multi-performance analysis and load experimental study of a 3-DOF over constrained robot with high energy efficiency for extracting fermented grains","authors":"Yubin Zhang ,&nbsp;Jinzhu Zhang ,&nbsp;Xiaoyan Xiong ,&nbsp;Shengxiang Liu ,&nbsp;Hongjie Du ,&nbsp;Yanjiang Huang","doi":"10.1016/j.robot.2025.105157","DOIUrl":"10.1016/j.robot.2025.105157","url":null,"abstract":"<div><div>In this paper, a novel 3-DoF hybrid mechanism is presented, as the manipulator of the reclaiming robot for the extraction process of fermented grains (FG) of liquor. and the performance analysis and motion control are studied. The performance is evaluated from three dimensions: motion/force transmission characteristics, speed characteristics, and dynamic characteristics, and the redundant complementary driving characteristics of this mechanism were analyzed. For the multi-closed-loop over-constrained mechanism, all the driving/constraining forces and torques are determined using a method that combines the Newton-Euler equation and deformation coordination equation. Additionally, the prototype of the reclaiming robot for FG is developed. In the robot's control system design, a collision observer based on second-order momentum and an active contact self-aligning trajectory algorithm are designed for the actuator-cylinder centering. Furthermore, an adaptive robust controller is designed for motion control. Finally, the experiments are conducted to test the trajectory tracking performance and analyze the unmodeled dynamic characteristics, which also show the advantages of energy efficiency and load performance of the mechanism. This paper serves as a basis for the design and analysis of the robot's hybrid over-constrained mechanism and provides an idea for the realization of force detection and position control.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105157"},"PeriodicalIF":5.2,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144826931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributed adaptive coverage control with obstacle avoidance for a drone network based on collective initial excitation","authors":"S. Surendhar ,&nbsp;Sayan Basu Roy ,&nbsp;Shubhendu Bhasin","doi":"10.1016/j.robot.2025.105135","DOIUrl":"10.1016/j.robot.2025.105135","url":null,"abstract":"<div><div>This paper introduces a distributed adaptive controller for mobile sensor network (MSN) coverage that incorporates collective initial excitation (C-IE) while simultaneously ensuring obstacle avoidance. Agents exchange their parameter estimates with their neighbors to facilitate consensus on the unknown sensory function. They collectively achieve the C-IE condition, which enables parameter convergence and obviates the need for every agent to individually satisfy the excitation condition. This C-IE condition extends the previously established initial excitation (IE) condition to multi-agent systems. The proposed artificial potential-like control law and parameter adaptation guarantee both obstacle avoidance and coverage, along with parameter estimation. Experimental tests with multiple drones validate the effectiveness of the proposed method.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105135"},"PeriodicalIF":5.2,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An embedded deep learning neural network control for a wheeled mobile robot","authors":"Ahmad M. El-Nagar ,&nbsp;Ahmad M. Zaki ,&nbsp;F.A.S. Soliman ,&nbsp;Mohammad El-Bardini","doi":"10.1016/j.robot.2025.105154","DOIUrl":"10.1016/j.robot.2025.105154","url":null,"abstract":"<div><div>This paper proposes an adaptive tracking scheme for a 4-wheeled skid steering mobile robot (4-WSSMR) using diagonal recurrent neural network controller based on the hybrid deep learning algorithm (DRNNC-HDLA). For the developed DRNNC-HDLA structure, the diagonal recurrent neural network is constructed, whose initial weights values are obtained through the hybrid deep learning algorithm. It is a combination of the restricted Boltzmann machine and the self-organized map of Kohonen. The network weights and learning rate for the proposed scheme are updated based on the Lyapunov stability criteria to achieve the controlled system stability. To show the robustness of the proposed algorithm, the results are compared to other existing algorithms. The proposed algorithm is practically implemented for controlling a 4-WSSMR to show the ability of the proposed algorithm to deal with real applications. The effectiveness of the proposed approach is validated through extensive real-world experiments involving uncertainties and disturbances, demonstrating its capability to achieve accurate and reliable trajectory tracking. This work advances the field by offering a reliable control solution for mobile robots operating under challenging conditions.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105154"},"PeriodicalIF":5.2,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144826751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning-aided state estimation for robotic rollators with experimental validation","authors":"Abdullah Yeaser ,&nbsp;James Tung ,&nbsp;Jan Huissoon ,&nbsp;Ehsan Hashemi","doi":"10.1016/j.robot.2025.105140","DOIUrl":"10.1016/j.robot.2025.105140","url":null,"abstract":"<div><div>While demand for assistive technology has risen with aging populations and concomitant increase in mobility disabilities, conventional (passive) walker designs have demonstrated safety and usability limitations. Robotic rollators (or 4-wheeled walkers) have been proposed to address concerns, including slip, fall, and collision risks. To develop control systems for robotic rollators, accurate estimation of the states is required. While model-based estimation approaches have been widely investigated for mobile robots, robotic rollators present unique challenges due to model parameter changes and uncertainties. In contrast, data-driven estimation approaches require sufficient excitation modes during learning to address corner cases. The proposed learning-aided state estimation (L-ASE) method augments an unscented transformation observer with a long short term memory (LSTM) based learning algorithm to estimate rollator states by using on-board inertial measurement unit data and wheel speeds. The stability and boundedness of the error covariance is investigated. The developed learning-aided estimation method is also experimentally verified for the walker-assisted gait and demonstrates superior performance using a robotic rollator platform in rigorous testing conditions.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105140"},"PeriodicalIF":5.2,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pro-routing: Proactive routing of autonomous multi-capacity robots for pickup-and-delivery tasks","authors":"Daniel Garces,&nbsp;Stephanie Gil","doi":"10.1016/j.robot.2025.105138","DOIUrl":"10.1016/j.robot.2025.105138","url":null,"abstract":"<div><div>We consider a multi-robot setting, where we have a fleet of multi-capacity autonomous robots that must service spatially distributed pickup-and-delivery requests with fixed maximum wait times. Requests can be either scheduled ahead of time or they can enter the system in real-time. In this setting, stability for a routing policy is defined as the cost of the policy being uniformly bounded over time. Most previous work either solve the problem offline to theoretically maintain stability or they consider dynamically arriving requests at the expense of the theoretical guarantees on stability. In this paper, we aim to bridge this gap by proposing a novel proactive rollout-based routing framework that adapts to real-time demand while still provably maintaining the stability of the learned routing policy. We derive provable stability guarantees for our method by proposing a fleet sizing algorithm that obtains a sufficiently large fleet that ensures stability by construction. To validate our theoretical results, we consider a case study on real ride requests for Harvard’s Evening Van System, a university-wide minibus transportation service that allows students to book rides within an operational area around the campus. We also evaluate the performance of our framework using the currently deployed smaller fleet size under no traffic and average traffic conditions. In this smaller setup, we compare against the currently deployed routing algorithm, greedy heuristics, and Monte-Carlo-Tree-Search-based algorithms. Our empirical results show that our framework maintains stability when we use the sufficiently large fleet size found in our theoretical results. For the smaller currently deployed fleet size, our method services 15% more requests than the closest baseline while reducing median passenger wait times by 33%.</div></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"194 ","pages":"Article 105138"},"PeriodicalIF":5.2,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144860517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}