Mechatronics最新文献

Automatic rehabilitation equipment provides timely and effective rehabilitation training, which is critical in accelerating the recovery of joint injury and motion function. This paper proposes a novel cable-driven parallel robot for full-cycle ankle rehabilitation considering large angle, considerable moment, and multi-degree of freedom coupling. The configuration design, dimension optimization, control strategy, and prototype development are completed. By adopting rigid branch and cross cables, noticeable rotation angle and moment are achieved with a simple and lightweight configuration. Optimal design is implemented based on the grid search with the balance between the maximum cable force and the robot size. The control strategy that meets multiple training modes is developed, covering the entire rehabilitation cycle. Finally, the prototype is implemented to verify the research validity and provides high-performance rehabilitation equipment for the ankle joint.

In this paper, we propose an Isomorphic Mapping Reconfigurable Multi-Agent Reinforcement Learning (IM-RMARL) framework, which is suitable for decision-making scenarios in reconfigurable multi-agent reinforcement learning. This method holds promising applications in fields such as logistics transportation systems and disaster relief. Classical multi-agent frameworks typically assume that the number of agents is fixed and remains constant throughout the training process. However, in practical applications involving reconfigurable robots, the number of agents may vary over time or according to task requirements. Additionally, classical frameworks often assume easy access to abundant experience data for training and optimization. However, in reconfigurable robot clusters, this assumption may not hold true as not all combinations exist within a single episode. Our approach effectively addresses these challenges by integrating agent mapping mechanisms and similar type of intelligent agents’ experience sharing mechanisms, which aid in handling dynamic agent counts and limited experience data. Our experimental results demonstrate the effectiveness of the proposed framework, the Utilization Rate of Transport Capacity of the IM-RMARL group reaches 0.82, and the Task Completion Rate reaches 0.92.

Collaborative haptic training systems offer numerous benefits, including enhanced safety, streamlined training processes, and improved maneuverability. These systems typically involve an expert user (the trainer) and a novice user (the trainee) engaging in collaborative operations. One of the primary challenges in designing controllers for such systems is ensuring task stability and maintaining stable interaction between the operators and the system, while also achieving satisfactory task performance. However, existing control schemes often overlook the need for supervision and intervention by the trainer during the operation, along with a comprehensive stability analysis. This article aims to address the above issues for a system in which the trainee conducts the operation and the trainer is provided with the capability to intervene and modify the incorrect actions of the trainee. This is accomplished through the implementation of impedance controllers at each haptic interface and dynamic adjustment of the target impedance on both ends based on the trainer’s estimated impedance gain. The Input-to-State Stability approach and the small gain theorem are employed to analyze the stability of the closed-loop system. The effectiveness of the proposed approach is demonstrated through simulation and experimental results, showcasing the ability of the proposed scheme to enhance the collaborative training process and ensure stable interaction between the trainer and the trainee.

Given the limited availability of off-the-shelf continuum robots (CRs), researchers and engineers must design their own and tailor them to their specific use case requirements. Questions such as the following arise: What is the minimum length of the CR needed to achieve the desired dexterous workspace? And where should the robot be ideally located with respect to the workspace? These questions are answered for a single-port setup in this paper. A projection-based method is introduced that maps the dimensionality of the required workspace from 3D to 1D, exploiting the remaining degrees of freedom preserved in a single-port procedure. Then, a set of equations for the most critical point in the workspace is described, representing the geometry of both the CR and the workspace. A bounded, non-linear optimization approach is implemented, computing the global minimum of this set of equations. This method is simulated and tested for a length-extensible, multi-backbone CR. To the best of the authors’ knowledge, this is the first time a desired dexterous workspace has been empirically verified for a CR. Furthermore, the prototype features novel design elements that solve relevant mechanical challenges in the state-of-the-art

The concept of a nano-laboratory inside an SEM involves performing a sequence of tasks in a continuous pattern. Robotic systems with nanoscale motion resolution facilitate in-situ manipulation and characterization of nanomaterials to assemble nanodevices inside SEMs. Precise motion control of micromanipulators is required at both macro and micro-nano scales to effectively execute multiple sequential experimental tasks in nanofabrication. However, managing the entire nanomanipulation setup is challenging due to the constricted workspace inside an SEM and the lack of proper process feedback information at that scale. This study explores the application of path planning algorithms to generate a collision-free motion path for the micromanipulators operating within the confined space of an SEM. A MATLAB-based computational tool is first developed using PRM and Dijkstra's path planning algorithms. Considering environmental constraints, the program generates an optimal motion path for the micromanipulators, facilitating automatic configuration changes within the SEM chamber. It ensures a seamless workflow and facilitates the smooth integration of additional experimental tools within the existing setup. Manipulation strategies using the nanorobotic setup are established based on the application of the developed path planning module. A pick-and-place 3D nanomanipulation technique of CNTs using cooperative control of dual micromanipulators has been demonstrated for nanodevice construction. Additionally, the electrical response of individually manipulated CNTs is recorded using a two-probe measurement technique.

The planar tape-spring hyper-redundant manipulator presented in this paper is mainly constructed from tape springs, fixed-drive components, and mobile-drive components. It not only has high robustness and excellent transformability, but also high packaging efficiency. However, when the manipulator extends to a long range in motion experiments, some segments of the tape springs buckle. To address this drawback, a kinematic model of the planar tape-spring hyper-redundant manipulator is established, and, a configuration planning method based on a virtual spring model is proposed to solve the inverse kinematics problem. To enhance stability, the column stability is then incorporated into the configuration planning model. This approach relies on only configuration planning to prevent buckling. An alternative approach of adding auxiliary rods into the manipulator is also proposed. With this method, extra intermediate supports have been added to the manipulator. The effective column length of some segments is shortened, which effectively increases the critical buckling load of those segments of the tape spring. Finally, a prototype was subjected to motion and stability experiments to validate the presented approaches and analysis.

A cable-driven manipulator demonstrates significant application in cramped environments, such as space maintenance and equipment monitoring, owing to its slender body and excellent flexibility. However, in traditional designs, the mapping between the operational space and the joint space is nonlinear and non-consistent, and the driving cables are also coupled. Consequently, the kinematics and dynamics become highly complex, posing challenges in enhancing efficiency and precision in trajectory planning and control. This paper introduces a novel linear decoupling cable-driven manipulator with independent driving joints. Two sets of nonlinear transmission mechanisms are designed and serially connected to form an equivalent linear transmission mechanism. This arrangement establishes a proportional relationship between the motor angle and joint angle, with the proportionality coefficient representing the equivalent transmission ratio. Moreover, a two-way wire-pulling mechanism is designed to achieve one-to-one driving between the motor and the joint. The nonlinear coupling problem between driving cables is solved by connecting the driving cable to the target joint through a constant-length cable sleeve. Based on the aforementioned design, the linear and consistent mapping between the operational space and the joint space is realized, significantly simplifying the kinematic model. Prototype experiments validate the manipulator's extensive range of motion and high motion accuracy.

In recent years, there has been significant progress in developing specialized 3D printing techniques that cater to various demanding applications. However, the current state of this technology is challenged when it comes to complex in situ printing scenarios, which require a controlled printing platform. The lack of a stable printing platform is a fundamental limitation of its use in in situ applications. To address this issue, we present a novel platform-independent 3D fabrication process that enables printing on platforms with non-cooperative movement. The process overcomes the challenge of high-speed tracking, motion compensation, and real-time printing by developing a closed-loop visual feedback-controlled robotic printing process. The proposed process incorporates a marker-based visual detection and tracking controller setup, which is discussed in detail. The algorithm consists of two loops running asynchronously: a high-speed inner control loop and an outer measurement loop. This setup enables precise and accurate tracking of the printing platform, compensating for any disturbances during the printing process. Our experimental results demonstrate the successful printing of simple linear geometries, even with low-disturbing platform velocities. Moreover, the tracking controllers' ability to handle measurement occlusion is validated, showing the proposed process's robustness and effectiveness. Our work provides a significant step towards enabling 3D printing in complex in situ printing scenarios.

This article presents an experimental validation of a model predictive path-following control algorithm (PF-MPC ) applied to a truck–trailer system, encompassing both forward and backward motions. The proposed controller is designed to precisely follow a predefined path generated by a path planner, with a designated guidance point positioned on either the truck or the trailer. The algorithm’s performance is assessed through implementation and validation on a model-scaled truck–trailer system, where MPC, state estimation, and low-level control are executed on a microcontroller (MCU ). The experimental results demonstrate the effectiveness of the proposed control approach in achieving highly accurate path-following performance, even when operating in the challenging context of unstable backward motion, and with the involvement of up to two trailers. Moreover, the successful implementation of the algorithm on a microcontroller underscores its suitability for real-time control applications. The results of this study collectively highlight the promising potential of the proposed control algorithm for practical utilization in autonomous driving systems.

Fluctuations in oil temperature, changes in friction plate temperature, and friction plate wear significantly influence the precision of torque control in wet clutches, consequently impacting vehicle launch and gear shift quality. In this study, we introduce a novel approach for estimating the dynamic friction coefficient of wet clutches and develop a feedforward torque controller tailored to dual-clutch transmissions. This controller adeptly compensates for the effects of oil temperature variations, friction plate temperature shifts, and wear. We also incorporated an observer for real-time estimation of clutch torque. The dynamic friction coefficient of the clutch is continuously estimated using models that account for the influence of oil temperature, friction plate temperature, and service mileage. Leveraging this estimated dynamic friction coefficient, the clutch torque is precisely controlled during slip engagement. Our co-simulation results affirm the accuracy of the controller presented in this paper. Even after changes in factors affecting friction coefficients, it consistently maintains control precision, surpassing non-adaptive controllers based on pressure-torque and pressure-speed difference-torque models. Bench testing further validates the controller's accuracy in torque control and its adaptability to fluctuations in oil temperature, friction plate temperature, and wear.