International Journal of Intelligent Robotics and Applications最新文献

Long-stroke compliant parallel mechanisms (CPMs) are widely used in precision applications. However, stress stiffening and sensitivity to external disturbances in CPMs present challenges in the design of controller. In this paper, the nonlinear stiffness model of the stage is established which is incorporated into the dynamic model. In particular, the method of adaptive nonsingular fast terminal sliding mode control (ANFTSMC) is developed based on the dynamic model. This method addresses the problems of the system parameter uncertainty and the slow convergence of traditional sliding mode control (SMC) at the equilibrium point. The stability of the presented ANFTSMC strategy has been proved based on the Lyapunov analysis. Finally, the proposed control architecture is implemented on the designed 4-prismatic-prismatic-revolute (4-PPR) CPM. The results demonstrate that the developed method exhibits excellent tracking accuracy and robustness compared to the traditional linear sliding mode control (LSMC) and proportional-integral-derivative (PID) control.

Predicting human stiffness, especially at the distal end of the human arm, holds significant potential for various applications. It facilitates the realization of humanoid stiffness regulation in robots, improves the adaptability and human-likeness of interactive robots, and addresses critical issues in human control of medical assistive robots. Recognizing that surface electromyographic (EMG) signals not only contain rich information but are also easy to collect and process, they serve as an optimal choice for predicting human stiffness. To establish a mapping relationship between surface EMG signals and stiffness information, we constructed a stiffness acquisition system to collect signals such as EMG, angular, force, and displacement signals. Additionally, considering the influence of different angles (configurations) of the human arm on the stiffness at the distal end, we researched a stiffness prediction model for the distal end of the human arm using a multilayer perceptron. Experimental results demonstrate that our proposed stiffness prediction model, utilizing EMG information provided by the EMG armband along with angular information, can predict the stiffness at the distal end of the human arm in various scenarios. This provides ample reference for achieving humanoid stiffness regulation in medical assistive robots.

Lower limb exoskeletons play a pivotal role in augmenting human mobility and improving the quality of life for individuals with mobility impairments. In light of these pressing needs, this paper presents an improved control strategy for a 10-degree-of-freedom lower limb exoskeleton, with a particular focus on enhancing stability, precision, and robustness. To simplify the intricate dynamic model of the exoskeleton, our approach leverages a more manageable 2nd order ultra-local model. We employ two radial basis function (RBF) neural networks to accurately estimate both lumped disturbances and non-physical parameters associated with this ultra-local model. In addition, our control strategy integrates the backstepping technique and the super twisting algorithm to minimize tracking errors. The stability of the designed controller is rigorously established using Lyapunov theory. In the implementation phase, a virtual prototype of the exoskeleton is meticulously designed using SolidWorks and then exported to Matlab/Simscape Multibody for co-simulation. Furthermore, the desired trajectories are derived from surface electromyography (sEMG) measured data, aligning our control strategy with the practical needs of the user. Comprehensive experimentation and analysis have yielded compelling numerical findings that underscore the superiority of our proposed method. Across all 10 degrees of freedom, our controller demonstrates a significant advantage over alternative controllers. On average, it exhibits an approximately 45% improvement compared to the Adaptive Backstepping-Based -RBF Controller, a 74% improvement compared to the Model-Free Based Back-Stepping Sliding Mode Controller, and an outstanding 74% improvement compared to the Adaptive Finite Time Control Based on Ultra-local Model and Radial Basis Function Neural Network. Furthermore, when compared to the PID controller, our approach showcases an exceptional improvement of over 80%. These significant findings underscore the effectiveness of our proposed control strategy in enhancing lower limb exoskeleton performance, paving the way for advancements in the field of wearable robotics.

Aiming at the problems of low success rate, long time and tortuous path of the traditional Rapidly-exploring Random Trees series of algorithms for path planning, this paper proposes the optimal path sampling algorithm based on the potential function (AP-RRT*), which solves the path planning problem of the manipulator in three-dimensional space. First, the potential function is defined and the concept of sampling termination distance is proposed. Second, a secondary sampling strategy is proposed in combination with the potential function to improve the planning speed and increase the coverage rate. Third, adaptive weights and adaptive step size are used to dynamically adjust the planning direction and distance, thereby improving the planning efficiency. Moreover, when performing node reconnection, dynamic retrieval circles are set to ensure path quality while reducing computational consumption. Finally, the improved algorithm, along with other algorithms, is simulated and experimentally verified in MATLAB and ROS. The results show that the AP-RRT* algorithm is superior in terms of path length, planning time, iterations, number of waypoints and success rate.

Exploring large-scale environments autonomously poses a significant challenge. As the size of environments increases, the computational cost becomes a hindrance to real-time operation. Additionally, while frontier-based exploration planning provides convenient access to environment frontiers, it suffers from slow global exploration speed. On the other hand, sampling-based methods can effectively explore individual regions but fail to cover the entire environment. To overcome these limitations, we present a hierarchical exploration approach that integrates frontier-based and sampling-based methods. It assesses the informational gain of sampling points by considering the quantity of frontiers in the vicinity, and effectively enhances exploration efficiency by utilizing a utility function that takes account of the direction of advancement for the purpose of selecting targets. To improve the search speed of global topological graph in large-scale environments, this paper introduces a method for constructing a sparse topological graph. It incrementally constructs a three-dimensional sparse topological graph by dynamically capturing the spatial structure of free space through uniform sampling. In various challenging simulated environments, the proposed approach demonstrates comparable exploration performance in comparison with the state-of-the-art approaches. Notably, in terms of computational efficiency, the single iteration time of our approach is less than one-tenth of that required by the recent advances in autonomous exploration.

Abstract

With the advantages of high flexibility, high safety, and good adhesion and wrapping, soft robots have a wide range of application prospects in complex environments such as automatic production lines and medical surgery. By coupling an active pneumatic drive structure and an interference variable stiffness mechanism, this paper designs a soft robot based on a variable stiffness pneumatic actuator. Based on kinematic analysis and finite element simulation based on the segmented constant curvature method, the Lagrange equations are applied to perform dynamic analysis, which in turn verifies the variable stiffness performance and bending performance of the variable-stiffness soft robotic arm. The soft manipulator adopts the structural design based on 2 mm thickness, jamming mechanism and coupling fiber layer, which can effectively resist 0–2.5 N force without large deviation and be adjustable in the stiffness range of (0.025–0.12) N/mm, under the condition that the vacuum degree does not exceed 80 kPa. The stiff stiffness and bending behavior of the proposed soft manipulator show excellent performance and can be applied to industrial automation, medical devices and other operations.

Abstract

The parametric variations and external perturbations in the coupled subject-exoskeleton system delay and hinder effective gait tracking in clinical rehabilitation. This problem becomes more challenging in the case of the pediatric exoskeleton system. In this work, to address this benchmark challenge, a fast terminal sliding mode with a rapid reaching law (FTSM-RRL) control scheme is introduced for an uncertain lower-extremity exoskeleton aimed at assisting pediatric gait under different walking speeds. At first, the computer-aided design of the gait exoskeleton system is demonstrated with details of the desired gait trajectories of a male boy aged 12 years (weight: 40 kg, height: 132 cm). A fast terminal sliding mode controller is proposed with a varied exponential approaching rule to guarantee the rapid convergence of system states on the sliding manifold and then towards the origin in a finite period. After that, an upper limit criterion is involved within the reaching control law to compensate for the adverse effects of uncertainties and disturbances as a lumped parameter. Lyapunov’s theory is presented to ensure the expeditious convergence of the tracking error in the reaching and sliding phases. The proposed FTSM-RRL strategy is incorporated to obtain the desired trajectory tracking at slow, self-selected, and fast walking speeds. From numerical experiments, the proposed FTSM-RRL controller is found to be consistently effective ( (> 71%) in X-direction and (> 62%) in Y-direction) over the PID controller and ( (> 7%) in X-direction and (> 10%) in Y-direction) over the FTSM-ERL controller. In joint space, the proposed FTSM-RRL control consistently surpasses both PID and FTSM-ERL controls in tracking hip movement. While the proposed controller outperforms PID and FTSM-ERL for knee joint tracking, the extent of improvement diminishes at higher speeds. For ankle joint tracking, the proposed control exhibits substantial enhancement at slow speeds but comparatively poorer performance at self-selected and fast speeds when compared to PID control. However, FTSM-RRL consistently outperforms FTSM-ERL across all speeds for ankle joint tracking. Compared to FTSM-ERL control, the proposed FTSM-RRL control accelerates the hip and knee joint sliding surface convergence by 0.52s and 0.24s (slow walking), 0.55s and 0.33s (self-selected walking), and 0.61s and 0.09s (fast walking). The results obtained in this study ensure fast and efficient passive-assist gait training for the pediatric groups using exoskeleton technology.

Incremental sheet forming (ISF) is a highly versatile and flexible process for small batch production of complex sheet metal parts. Since, there is no die used in the process, the accuracy of the parts formed is an area of concern in ISF. In the current work, an experimental set-up was developed for robot assisted incremental sheet hydroforming (RAISHF) and was conducted on AA3105 to fabricate different shapes. Formability by RAISHF was found to be better than robot assisted incremental sheet forming (RAISF) due to fluid pressure from the back of the sheet which can be impart more ductility to the sheet. Additionally, a more uniform thickness was achieved by the RAISHF. A variable wall angle conical frustum (VWACF) was fabricated by each process and their formability was compared. The maximum wall angle before the onset of fracture was 73° and 64° by the process of RAISHF and RAISF, respectively. Also the thickness along the length of the cone was more uniform by RAISHF than RAISF. Further, the effect of curvature on mechanical properties and surface finish of the formed product by RAISHF was examined by fabricating a rhomboidal and conical frustums of a fixed wall angle of 45°. Tensile test and surface finish test were conducted on the samples taken from the two types of frustums. Mechanical properties and surface finish were found better of the rhomboidal frustum due to flat wall.

An exosystem needs to be nonlinear when it generates the perturbations to be reconstructed; however, an exosystem does not need to be nonlinear when it generates the references to be tracked. Resulting that the tracking of the references generated by an exosystem is an easier task. Hence, some studies on the references tracking should be made. Furthermore, to solve the references tracking, the perturbations are needed. In this research, the references tracking and the perturbations reconstruction in a Cartesian robot are discussed. For the perturbations reconstruction, an estimator is defined to force the reconstructed perturbations to track the perturbations of a Cartesian robot model. For the references tracking, a controller is defined to force a Cartesian robot model to track an exosystem. A theorem is addressed to prove the perturbations reconstruction. A theorem is addressed to prove the references tracking. A simulation in a Cartesian robot is used to confirm the validity and effectiveness of our controller with estimator in comparison with a feedback controller.

Robot systems often face highly nonlinear manipulator dynamics and uncertainties such as external disturbances, payload variations, and end effector modeling errors. Therefore, it is of great industrial importance to compute and simulate the dynamic response of these manipulators in a reliable manner. This research investigates a robust control strategy—Integral Sliding Mode Control (ISMC)—applied to a three-degree-of-freedom robot manipulator with external disturbances. The study consists of two stages. The first stage uses Proportional-Derivative (PD) control with dynamically calculated weight values in the absence of the external disturbances. In the second stage, ISMC is employed to address dynamic responses to disturbances. The computation work on the model is implemented in Mathematica software, and a three-joint SCARA-type robot is tested to demonstrate methodology robustness. In the end, stability is ensured through Lypunove function analysis and the sliding surface's phase portrait.