Robotics and Autonomous Systems最新文献_第2页

Motion priority optimization framework towards automated and teleoperated robot cooperation in industrial recovery scenarios

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems

Pub Date : 2025-02-01 DOI: 10.1016/j.robot.2024.104833

Shunki Itadera, Yukiyasu Domae

In this study, we introduce an optimization framework to enhance the efficiency of motion priority design in scenarios involving automated and teleoperated robots within an industrial recovery context. The increasing utilization of industrial robots at manufacturing sites has been instrumental in reducing human workload. Nevertheless, achieving effective human–robot collaboration/cooperation (HRC) remains a challenge, especially when human workers and robots share a workspace for collaborative tasks. For instance, when an industrial robot encounters a failure, such as dropping an assembling part, it triggers the suspension of the corresponding factory cell for safe recovery. Given the limited capacity of pre-programmed robots to rectify such failures, human intervention becomes imperative, requiring entry into the robot workspace to address the dropped object while the robot system is halted. This discontinuous manufacturing process results in productivity loss. Robotic teleoperation has emerged as a promising technology enabling human workers to undertake high-risk tasks remotely and safely. Our study advocates for the incorporation of robotic teleoperation in the recovery process during manufacturing failure scenarios, which is referred to as “Cooperative Tele-Recovery”. Our proposed approach involves formulating priority rules designed to facilitate collision avoidance between manufacturing and recovery robots. This, in turn, ensures a continuous manufacturing process with minimal production loss within a configurable risk limitation. We present a comprehensive motion priority optimization framework composed of an HRC simulator and a cooperative multi-robot controller to identify optimal parameters for the priority function. The framework dynamically adjusts the allocation of motion priorities for manufacturing and recovery robots while adhering to predefined risk limitations. Through quantitative and qualitative assessments, we validate the novelty of our concept and demonstrate its feasibility.

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引用次数: 0

Path planning strategy for a space relocatable robotic manipulator based on improved GBNN algorithm

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems

Pub Date : 2025-02-01 DOI: 10.1016/j.robot.2025.104939

Yidao Ji, Cheng Zhou, Ruiyi Lin, Qiqi Liu

For the purpose of assisting astronauts in performing specific operations on orbital space stations, the space relocatable robotic manipulator has been studied and applied by many countries. In practical application scenarios, achieving optimal mobility and resource efficiency are the primary technical requirements for this manipulator. Therefore, we have developed an improved path-planning strategy based on the Glasius Bio-inspired Neural Network algorithm. This approach reduces computational resource consumption, dynamically avoids obstacles, and accounts for physical constraints. To simplify the complex process of 3D map rasterization, our method directly abstracts and constructs a topologically connected graph for the grasping points. Furthermore, the improved algorithm enhances the energy efficiency of path planning by incorporating a function that integrates global information. It also employs a diffusive updating method, enabling the rapid propagation of neuron activity values to target points within a single iteration. To further advance the practical application of the algorithm, we have considered the kinematic properties and physical constraints of the manipulator. Finally, we developed a dual-layer planning strategy that enables the manipulator to move efficiently across the surface of a non-regular space station. The effectiveness and advantages of the improved algorithm have been thoroughly evaluated through comprehensive comparisons with existing algorithms.

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引用次数: 0

Entropy-based tuning approach for Q-learning in an unstructured environment

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems

Pub Date : 2025-01-31 DOI: 10.1016/j.robot.2025.104924

Yu-Jen Chen , Wei-Cheng Jiang

In reinforcement learning applications, achieving a balance between exploration and exploitation is a crucial problem during the learning process. This study proposes an entropy-based tuning approach that uses the value different based exploration theory is proposed to solve this problem in an unstructured environment. In such an environment, a learning agent can manage its exploration rates in each state instead of using a constant rate for all states. Moreover, some obstacles may block the agent’s path to the destination. Accordingly, the proposed approach enables the agent to adaptively increase its exploration rates in some states undergoing transitions; thus, the agent is encouraged to explore in those states. This paper presents simulations of maze environments and the car parking problem to verify the proposed approach. The simulation results demonstrate that our approach enables the agent to adjust its policy quickly to adapt to changing environments.

引用次数: 0

Aerial-ground testbed for simulating compliant bimanual on-orbit operations: From aerial to space robotic manipulation

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems

Pub Date : 2025-01-29 DOI: 10.1016/j.robot.2025.104927

Alejandro Suarez , Antonio Gonzalez-Morgado , Miguel Ruiz , Alejandro Lucena , Alessandro M. Giordano , Anibal Ollero

This paper presents the design and development of an aerial-ground robotics testbed for simulating bimanual manipulation operations on orbit relying on aerial robotics platforms, considering as representative use case the capture and maintenance of a non-cooperative free-floating satellite. The proposed testbed design is intended to facilitate the realization of simulations involving physical interaction, taking benefit of the technologies derived from aerial robotic manipulation, to be used as a complementary or alternative solution to existing ground testbed facilities. The system consists of a fully actuated multi-rotor (FAMR) that emulates the free flying/free floating dynamics of a target satellite, and a lightweight and compliant anthropomorphic dual arm system (LiCAS) to conduct the manipulation task, implementing the dynamics simulation in Simscape Multibody. The human-size and human-like kinematics of the LiCAS allow to replicate the manipulation skills of human operators, whereas its very low weight (2.5 kg) makes it possible to mount it on lightweight industrial robotic arms used to reproduce the spacecraft motion. Two types of compliant interactions are considered. On the one hand, impedance control for the post-contact phase is implemented in the simulation layer, using the right arm to hold the target and maintain the relative pose with the base while the left arm conducts the manipulation task. On the other hand, collision detection and passive accommodation is evaluated in the physical testing system relying on the mechanical joint compliance of the LiCAS dual arm. Collision reflexes between the free-floating FAMR and the compliant arm will be also experimentally evaluated by applying the principle of momentum conservation on the multi-rotor. The proposed approach takes benefit of the similarities between space and aerial robotic manipulation in terms of dynamic modeling, presenting simulation and experimental results in an indoor testbed to validate the developed framework.

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引用次数: 0

Tightly-coupled LiDAR-IMU-wheel odometry with an online neural kinematic model learning via factor graph optimization

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems

Pub Date : 2025-01-28 DOI: 10.1016/j.robot.2025.104929

Taku Okawara , Kenji Koide , Shuji Oishi , Masashi Yokozuka , Atsuhiko Banno , Kentaro Uno , Kazuya Yoshida

Environments lacking geometric features (e.g., tunnels and long straight corridors) are challenging for LiDAR-based odometry algorithms because LiDAR point clouds degenerate in such environments. For wheeled robots, a wheel kinematic model (i.e., wheel odometry) can improve the reliability of the odometry estimation. However, the kinematic model suffers from complex motions (e.g., wheel slippage, lateral movement) in the case of skid-steering robots particularly because this robot model rotates by skidding its wheels. Furthermore, these errors change nonlinearly when the wheel slippage is large (e.g., drifting) and are subject to terrain-dependent parameters. To simultaneously tackle point cloud degeneration and the kinematic model errors, we developed a LiDAR-IMU-wheel odometry algorithm incorporating online training of a neural network that learns the kinematic model of wheeled robots with nonlinearity. We propose to train the neural network online on a factor graph along with robot states, allowing the learning-based kinematic model to adapt to the current terrain condition. The proposed method jointly solves online training of the neural network and LiDAR-IMU-wheel odometry on a unified factor graph to retain the consistency of all those constraints. Through experiments, we first verified that the proposed network adapted to a changing environment, resulting in an accurate odometry estimation across different environments. We then confirmed that the proposed odometry estimation algorithm was robust against point cloud degeneration and nonlinearity (e.g., large wheel slippage by drifting) of the kinematic model. The summary video is available at: https://www.youtube.com/watch?v=CvRVhdda7Cw

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引用次数: 0

The Soft-PVTOL: Modeling and control

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems

Pub Date : 2025-01-27 DOI: 10.1016/j.robot.2025.104925

Gerardo Flores , Mark W. Spong

This paper introduces, for the first time, the soft planar vertical take-off and landing (Soft-PVTOL) aircraft. Unlike conventional PVTOL and multi-rotor systems, where position alterations inevitably impact orientation due to their underactuated design, the Soft-PVTOL offers the unique advantage of decoupling these dynamics, enabling unprecedented maneuverability and precision. We have demonstrated that the Soft-PVTOL can be accurately modeled using the Euler–Lagrange framework under a constant curvature assumption for the soft arms. This approach provides a significant advantage for designing control strategies tailored explicitly for soft aerial robots, offering a concise and singularity-free mathematical model that accurately captures the system’s dynamics. Furthermore, the model’s flexibility supports extensions to multiple constant curvature segments per arm, allowing scalability to more complex configurations and further broadening its applicability to the field of soft aerial robotics. Having demonstrated that the Soft-PVTOL satisfies the passivity property under our model, we designed a passivity-based control law to ensure global exponential convergence of the tracking error. Numerical simulations, including perturbations affecting the system, validate the robustness of the proposed approach, demonstrating effective trajectory tracking and decoupled position-orientation control, even under adverse conditions. These results demonstrate the Soft-PVTOL’s adaptability and maneuverability, marking a significant advancement in aerial robotics and establishing a foundation for future research into more sophisticated and versatile soft aerial robot designs.

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引用次数: 0

Kinematics characteristic analysis of a type of human-machine compatible ankle rehab robots based on human-ankle IFHA identification

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems

Pub Date : 2025-01-27 DOI: 10.1016/j.robot.2024.104911

Jingke Song, Jianjun Zhang, Jun Wei, Chenglei Liu, Xiankun Zhao, Cunjin Ai

Existing ankle rehabilitation robots lack reference to the actual ankle motion posture of humans, leading to a mismatch with the natural motion of the ankle joint and affecting the rehabilitation outcome. This paper uses screw theory and motion capture equipment to identify the instantaneous finite helical motion axis (IFHA) of the human ankle and obtains the distribution law of the instantaneous rotational axis and translational pitch of the ankle, and based on this, design a human-machine motion compatible rope-driven ankle joint rehabilitation robot that aligns with human motion for ankle joint rehabilitation. Firstly, the experimental trajectories of human ankle dorsiflexion(DF) /plantarflexion(PF), inversion(IN)/ eversion(EN), and adduction(AD)/abduction(AB)/ are taken by using the VICON motion capture system, and the experimental data are analyzed and processed according to the screw theory. The distribution law of the IFHA and the range of twist pitch (TP) are obtained. Secondly, according to the motion characteristics of the ankle joint obtained from the experiment, the constraint characteristics of the ankle rehabilitation mechanism are obtained, and it is mapped into a series of parallel mechanisms to meet the rehabilitation needs. Select a configuration as the skeleton of the robot, design a prototype of the novel rope-driven rehabilitation robot, and establish its kinematic model. Then, analyze the kinematic characteristics of the mechanism by combining screw theory and spatial analytic geometry theory. Finally, the experimental platform of the ankle rehabilitation robot is built to verify the accuracy of human-machine motion fitting, safety, comfort, and effectiveness of the rehabilitation robot.

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引用次数: 0

Time-bounded planning with uncertain task duration distributions

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems

Pub Date : 2025-01-25 DOI: 10.1016/j.robot.2025.104926

Michal Staniaszek , Lara Brudermüller , Yang You , Raunak Bhattacharyya , Bruno Lacerda , Nick Hawes

We consider planning problems where a robot must gather reward by completing tasks at each of a large set of locations while constrained by a time bound. Our focus is problems where the context under which each task will be executed can be predicted, but is not known in advance. Here, the term context refers to the conditions under which the task is executed, and can be related to the robot’s internal state (e.g., how well it is localised?), or the environment itself (e.g., how dirty is the floor the robot must clean?). This context has an impact on the time required to execute the task, which we model probabilistically. We model the problem of time-bounded planning for tasks executed under uncertain contexts as a Markov decision process with discrete time in the state, and propose variants on this model which allow adaptation to different robotics domains. Due to the intractability of the general model, we propose simplifications to allow planning in large domains. The key idea behind these simplifications is constraining navigation using a solution to the travelling salesperson problem. We evaluate our models on maps generated from real-world environments and consider two domains with different characteristics: UV disinfection, and cleaning. We evaluate the effect of model variants and simplifications on performance, and show that policies obtained for our models outperform a rule-based baseline, as well as a model which does not consider context. We also evaluate our models in a real robot experiment where a quadruped performs simulated inspection tasks in an industrial environment.

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引用次数: 0

An integral terminal sliding mode-based adaptive control approach for traversing unknown inclined surfaces

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems

Pub Date : 2025-01-24 DOI: 10.1016/j.robot.2025.104928

Lin Zhang , Lei Chen , Muhammad Saqib , Baoyu Wang , Pengjie Xu , Yanzheng Zhao

Skid-steering control is commonly used in mobile robots, but its application to climbing manipulation-oriented robots (CMo-R) requires further development. This study proposes an adaptive skid-steering control strategy using an integral terminal sliding mode controller (ITSMC) to improve the climbing maneuverability of four-wheeled CMo-Rs on unknown inclined surfaces. The control law is developed using both kinematics and dynamics models, considering slipping effects to reduce slippage during 3D motion. A slip estimation and ITSMC-based adaptive control algorithm are introduced to enhance tracking accuracy in complex 3D environments. The proposed approach is compared to traditional PID and adaptive kinematic controllers through simulations and experiments. Results show that the proposed method outperforms the others in terms of tracking performance and robustness, especially for navigating horizontal, inclined, and vertical surfaces. This work provides a new control strategy for CMo-Rs, contributing to the feasibility and stability of future climbing manipulation applications.

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引用次数: 0

Efficiency-optimized path planning algorithm for car-like mobile robots in bilateral constraint corridor environments

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems

Pub Date : 2025-01-22 DOI: 10.1016/j.robot.2025.104923

Junkui Zhong , Deyi Kong , Yuliang Wei , Xiaojuan Hu , Yang Yang

In the field of mobile robot path planning, optimizing mobility efficiency is paramount for enhancing operational productivity. This paper presents a novel path planning algorithm designed to optimize mobility efficiency. The algorithm generates free paths and employs turning points for segmentation, while Dubins and clothoid curves are utilized for path smoothing within kinematic constraints. An evaluation function, considering dynamic variables like velocity loss and distance traveled during turning, selects the optimal path for mobility efficiency. Experimental results reveal that the shortest path in length is not always the most efficient. Comparative analysis with the Hybrid A* algorithm showcases the proposed algorithm’s ability to generate smooth paths across various constraint environments, thereby enhancing robot mobility. Validation experiments on a custom-developed three-wheeled mobile robot confirm the effectiveness of the derived paths. This efficiency-optimized path planning algorithm finds practical application in settings such as factories with dual-boundary constraints and intricate corner configurations, offering time-saving trajectories to bolster overall robot operational efficacy.

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引用次数: 0