Mechatronics最新文献

Compliant movement and stress buffering of the torso are particularly important for state transition during high-speed locomotion in quadrupedal mammals. Currently, passive compliant control is commonly used in bionic torsos of quadruped robots, while active compliant control remains rare and immature. In previous research, we developed an active six-Degree-of-Freedom (DoF) bionic parallel torso. In this paper, we establish a muscle model that includes four biomechanical elements representing muscle characteristics (muscle force-fiber length and muscle velocity relationships) from the perspective of biology and physiology. We propose a musculoskeletal model that simulates the biological motion control system to control the compliant movement of each joint of the parallel mechanism. This model includes: 1) a neural equilibrium point controller that represents the transmission of motion commands, 2) activation dynamics that describe the activation of stimulated muscles, 3) contraction dynamics that emphasize the biomechanical characteristics of muscle tendons, 4) skeletal dynamics that describe bone movement. The effects of flexor and extensor stimulation on muscle activation, force, length, and velocity were analyzed. The results showed that both the flexor and extensor muscles will contract after corresponding stimulation. Furthermore, adjusting muscle stimulation through the musculoskeletal model can drive the parallel mechanism to reach the desired position. The musculoskeletal control method based on external force feedback can establish new torque balance in joints and drive the parallel torso to achieve compliant movements. Simulation and experiments have demonstrated the feasibility of the musculoskeletal control method. This method enhances the compliance and environmental adaptability of the parallel torso in practical applications.

This paper introduces the concept of underactuated vacuum gripper (UVG), which combines two strategies, that is, underactuation and vacuum grasping. The idea is to achieve shape adaptation while improving grip stability by augmenting an underactuated gripper with suction cups. A general theory to predict the contact forces for a UVG is developed and used for comparison reasons with a standard underactuated counterpart. Multibody simulations have been performed to verify the analytical model and quantitatively evaluate the performance of the system in terms of three metrics, namely, grasp stability, contact force distribution, and pull-out force. Finally, the experimental results obtained from a physical prototype of an underactuated linkage-driven gripper equipped with suction cups are illustrated, attesting to the feasibility and potential gain of the system.

Bilateral teleoperation is a network control system that connects distant locations under force sensation and contributes to task execution. The motivation of this study is to focus on the importance of symmetry in bilateral teleoperation systems and to design controller configurations with symmetry. This study employs the acceleration control-based four-channel bilateral teleoperation (AC4BT). AC4BTs have the regulator to zero in resultant force and the controller in positional difference, which can precisely achieve bidirectional force transmission and position synchronization while maintaining its symmetric structure. However, the coupled design of the force regulator and position controller remains challenging. The mutual impedance-based motion control approach derives and discusses the intrinsic wave dynamics in AC4BT under communication delay. The mutual impedance determines the transmission characteristics of force and position in bilateral teleoperation since it corresponds to the characteristic impedance in distributed-parameter systems. This study proposes the force-proportional-integral (force PI) and position-proportional-derivative (position PD) controllers, with the gain settings canceling the frequency-dependent terms. Without interfering with the realization of the control objectives, this brings the phase relationship between the force and velocity in manipulation closer to that performed in a no-delay situation. Experimental results verify the proposed approach.

Virtual holonomic constraints (VHCs) are extensively used in robotic applications such as bipedal walking. Although it is well-known that VHCs result in periodic motion of underactuated systems, achieving the same is challenging in physical systems due to parameter uncertainty. VHCs are typically imposed using feedback linearization and simulations show and experiments confirm that the internal dynamics can become unstable in the presence of parameter uncertainty. To address the challenging problem of generating stable periodic motion, we propose an extended high-gain observer (EHGO) based controller to enforce the VHCs. The proposed solution successfully recovers marginal stability of the internal dynamics. To stabilize a desired periodic orbit, we use the impulse controlled Poincaré map (ICPM) approach, where impulsive inputs are intermittently applied on a Poincaré section. Experimental results demonstrate that the model-based VHC controller and discrete ICPM controller together fail to stabilize the desired periodic motion but the EHGO-based VHC controller and ICPM controller successfully achieve stable periodic motion.

This paper describes the design of a robust controller for position control in systems with sandwiched backlash. The backlash, which is nonsmooth and nonlinear, is inevitable in the operation of many systems, but it can have destructive effects on the stability and performance of feedback systems. In this work, a robust controller is designed using a modified linear internal model control framework. Different controller architectures are considered and compared based on an experimental case study. The experimental testbased is composed of a three-platform structure driven by a stepper motor. The backlash is introduced into the system in a non-destructive and controllable manner by closing an internal nonlinear feedback loop around the stepper motor. The robustness of the designed controller to a large amount of backlash is verified experimentally, and while the stability is maintained, some residual vibrations are observed. The effects on the residual vibration levels of including nonlinear elements in the controller and changing the controller's settling time are also examined experimentally. The robustness to changes and mismodelling of the linear system, with and without the backlash, is described, as is the tracking of a smooth sinusoidal command signal with a growing amount of backlash. Based on the case study, it is concluded that combining the linear internal model control design method with a small dead zone results in a highly robust controller both with respect to the backlash and to changes in the linear system, which ensure stability and good performance. The required robustness is achieved by tuning the controller's settling time and the dead zone width parameters.

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.