This paper presents a continuum manipulator inspired by the anatomical characteristics of the elephant ***,the manipulator mimics the conoid profile of the elephant trunk,which helps to enhance its *** design features...
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This paper presents a continuum manipulator inspired by the anatomical characteristics of the elephant ***,the manipulator mimics the conoid profile of the elephant trunk,which helps to enhance its *** design features two concentric parts:inner pneumatically actuated bellows and an outer tendon-driven helical *** tendons control the omnidirectional bending of the manipulator,while the fusion of the pneumatic bellows with the tendon-driven spring results in an antagonistic actuation mechanism that provides the manipulator with variable stiffness and *** paper presents a new design for extensible manipulator and analyzes its stiffness and motion *** results are consistent with theoretical analysis,thereby demonstrating the validity of the theoretical approach and the versatile practical mechanical properties of the continuum *** impressive extensibility and variable stiffness of the manipulator were further demonstrated by performing a pin-hole assembly task.
When humanoid robots attempt to walk on terrain such as shaking platforms,time-varying disturbances are introduced to the support *** abrupt changes of inclination angle can cause the robot to lose balance upon landin...
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When humanoid robots attempt to walk on terrain such as shaking platforms,time-varying disturbances are introduced to the support *** abrupt changes of inclination angle can cause the robot to lose balance upon landing,presenting significant challenges for balance control *** address this issue,we propose a novel divergent component of motion(DCM)-based time-varying disturbance walking(DCM-TVDW)*** method allows the robot to walk on rugged surfaces and helps to maintain dynamic balance when subjected to large time-varying *** the DCM-TVDW control method,we first adjust the robot's center of mass and stride height to adapt to transitions between different terrain types via a variable height stabilization method,and hold these quantities constant as base *** then combine DCM with the N-step capturability *** combination allows for dynamic balance through multi-step adjustments from the initially unstable region,thereby extending the robots stability *** and experimental results demonstrate that the DCM-TVDW method enables the SJ-Bruce robot to traverse a dynamically shaking platform with an inclination angle of approximately 22°.
Analyzing and forecasting trajectories of agents like pedestrians plays a pivotal role for embodied intelligent applications. The inherent indeterminacy of human behavior and complex social interaction among a rich va...
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In this paper, a fault-tolerant-based online critic learning algorithm is developed to solve the optimal tracking control issue for nonaffine nonlinear systems with actuator ***, a novel augmented plant is constructed...
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In this paper, a fault-tolerant-based online critic learning algorithm is developed to solve the optimal tracking control issue for nonaffine nonlinear systems with actuator ***, a novel augmented plant is constructed by fusing the systemstate and the reference trajectory, which aims to transform the optimal fault-tolerant tracking control design with actuator faults into the optimal regulation problem of the conventional nonlinear error system. Subsequently, in order to ensure the normal execution of the online learning algorithm, a stability criterion condition is created to obtain an initial admissible tracking policy. Then, the constructed model neural network(NN) is pretrained to recognize the system dynamics and calculate trajectory control. The critic and action NNs are constructed to output the approximate cost function and approximate tracking control,respectively. The Hamilton-Jacobi-Bellman equation of the error system is solved online through the action-critic framework. In theoretical analysis, it is proved that all concerned signals are uniformly ultimately bounded according to the Lyapunov *** tracking control law can approach the optimal tracking control within a finite approximation error. Finally, two experimental examples are conducted to indicate the effectiveness and superiority of the developed fault-tolerant tracking control scheme.
Bio-inspired magnetic helical microrobots have great potential for biomedical and micromanipulation applications. Precise interaction with objects in liquid environments is an important prerequisite and challenge for ...
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Bio-inspired magnetic helical microrobots have great potential for biomedical and micromanipulation applications. Precise interaction with objects in liquid environments is an important prerequisite and challenge for helical microrobots to perform various tasks. In this study, an automatic control method is proposed to realize the axial docking of helical microrobots with arbitrarily placed cylindrical objects in liquid environments. The docking process is divided into ascent, approach, alignment, and insertion stages. First, a 3D docking path is planned according to the positions and orientations of the microrobot and the target object. Second, a steering-based 3D path-following controller guides the helical microrobot to rise away from the container bottom and approach the target along the path. Third, based on path design with gravity compensation and steering output limits, alignment of position and orientation can be accomplished simultaneously. Finally, the helical microrobot completes the docking under the rotating magnetic field along the target orientation. Experiments verified the automatic docking of the helical microrobot with static targets, including connecting with micro-shafts and inserting into micro-tubes. The object grasping of a reconfigurable helical microrobot aided by 3D automatic docking was also demonstrated. This method enables precise docking of helical microrobots with objects, which might be used for capture and sampling, in vivo navigation control, and functional assembly of microrobots.
The optimal control of nonlinear systems is crucial to improve system performance. However, the uncertainties of cost functions and systems dynamics make it difficult to solve the optimal control laws. To cope with th...
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Micro-cylindrical temperature sensors are crucial components for in-situ physiological signal monitoring in smart healthcare and minimally invasive surgical systems. However, due to the high-curvature complexity of th...
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Micro-cylindrical temperature sensors are crucial components for in-situ physiological signal monitoring in smart healthcare and minimally invasive surgical systems. However, due to the high-curvature complexity of the substrates, highprecision microfabrication on micro-cylindrical surfaces still faces significant challenges. This study proposes a microcylindrical electrohydrodynamic printing process to achieve on-demand high-resolution patterning on high-curvature surfaces with diameters ranging from 55 μm to 10 mm, addressing issues of mapping errors and stress concentration in array sensors integrated on micro-cylindrical surfaces. A physical model of micro-cylindrical electrohydrodynamic printing is established based on two-phase flow electrohydrodynamics to analyze the factors affecting the formation of stable cone-jets and the deposition of ink droplets on curved surfaces. Considering the elongated and high-curvature characteristics of micro-cylindrical objects, a printing system is designed with four degrees of freedom, coupling object rotation and translation. Numerical simulations reveal the patterns of electric field distortion caused by the horizontal offset of the nozzle relative to the vertical symmetry axis of the object, while experimental results identify the printing windows for inks of varying viscosities, voltages,and printing heights. Finally, a temperature sensor array is fabricated on the micro-cylindrical surface(sensor line width ~150 μm, lead wire width less than 50 μm, sensitivity ~0.00106), validating the consistency and stability of the array sensors and enabling temperature measurements in the range of 20℃-100℃. Additionally, the capability of the sensors array for temperature monitoring in simulated narrow cavity heating environments is demonstrated, exploring a novel method for fabricating advanced minimally invasive surgical instruments.
This paper investigates the prescribed-time tracking control problem for a class of multi-input multi-output(MIMO)nonlinear strict-feedback systems subject to non-vanishing uncertainties. The inherent unmatched and no...
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This paper investigates the prescribed-time tracking control problem for a class of multi-input multi-output(MIMO)nonlinear strict-feedback systems subject to non-vanishing uncertainties. The inherent unmatched and non-vanishing uncertainties make the prescribed-time control problem become much more nontrivial. The solution to address the challenges mentioned above involves incorporating a prescribed-time filter, as opposed to a finite-time filter, and formulating a prescribed-time Lyapunov stability lemma(Lemma 5). The prescribed-time Lyapunov stability lemma is based on time axis shifting time-varying yet bounded gain, which establishes a novel link between the fixed-time and prescribed-time control method. This allows the restriction condition that the time-varying gain function must satisfy as imposed in most exist prescribed-time control works to be removed. Under the proposed control method, the desire trajectory is ensured to closely track the output of the system in prescribed time. The effectiveness of the theoretical results are verified through numerical simulation.
The dynamic performance of the feed-drive system in CNC machine tools directly influences the accuracy of machined *** enhance the motion control performance of CNC machine tools,a high-precision model of the feed-dri...
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The dynamic performance of the feed-drive system in CNC machine tools directly influences the accuracy of machined *** enhance the motion control performance of CNC machine tools,a high-precision model of the feed-drive system is ***,current modeling methods for feed-drive systems seldom consider time-varying factors such as loads,wear,and *** a result,the model accuracy degrades when the system characteristics are affected by these time-varying *** this paper,a rolling optimization method with partial weights frozen is developed to realize quick iterative learning of a data-driven model for a feed drive system with time-varying characteristics using a small amount of ***,the long short-term memory fully connected(LSTM-FC)network is built and divided into feature extraction and output fitting parts based on their ***,a weight freezing-based rolling optimization method is *** weights in the feature extraction part are frozen,which preserves the learned common knowledge and patterns by solidifying the way that high-dimensional features are extracted from the *** adjusting the weights in the output fitting part,the extracted highdimensional features are remapped to the new data distribution changed by time-varying ***,the performance of the developed rolling optimization method is confirmed by *** results show that the proposed rolling optimization method reduces the maximum prediction errors by 49.5%and the total training time by 96.3%compared with existing methods,which demonstrates that the proposed method can restore model accuracy when the system characteristics change due to timevarying factors,and significantly accelerate the optimization process by rolling optimization.
Visuotactile sensors (VTSs) perceive tactile information through the elastomer deformation captured by the embedded camera. Markers are commonly added to the elastomer surface for VTS to get physical process sensing c...
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