Search Results (148)

Soft pneumatic actuators (SPAs) are widely used in applications requiring safe and compliant interaction; however, achieving bidirectional motion within a compact and predictable architecture remains a key challenge. Existing approaches typically rely on antagonistic actuator pairs or multi-chamber designs, which increase system complexity and control requirements, while single-chamber solutions often lack robust analytical models to predict their mechanical response. In this work, a Bidirectional Origami-Inspired Soft Pneumatic Actuator (Bi-OSPA) is proposed to achieve both elongation and contraction within a single-chamber structure, where the direction of motion is governed solely by the applied pressure (vacuum or positive). The actuator leverages origami-inspired geometry, allowing deformation to be primarily described through folding kinematics, which facilitates analytical modeling. An analytical framework is developed to predict actuator deformation as well as the corresponding elastic and output forces based on geometric parameters and pressure input, and is validated experimentally, showing good agreement across the displacement range. Furthermore, the effects of key design parameters on displacement and force output are investigated and characterized. The proposed Bi-OSPA combines structural predictive capability and bidirectional functionality, providing a foundation for the design and optimization of soft actuators. Its versatility is further demonstrated through applications in achieving pure twisting when integrated with a Kresling origami unit and as an actuation unit for a one-degree-of-freedom robotic finger enabling flexion and extension. Full article

To meet the high-precision and automated requirements for the insertion assembly between large-scale components and non-cooperative outer shells, an impedance-controlled large-component insertion assembly technology, namely compliant insertion assembly technology, is proposed. This paper explains the working principle of the technology from a theoretical perspective, elaborates on two key technical aspects—pose control and force-following control based on a parallel mechanism—and conducts horizontal insertion assembly simulation for components. The simulation results demonstrate that force-following control via the parallel mechanism can reduce the axial pose accuracy error between the component and the shell by more than 85%, meeting the pose accuracy requirements for insertion assembly. It is also verified that force-following control can adjust the pose of the shell in real time based on the coaxiality between the component and the shell, satisfying the minor deformation requirements during the insertion assembly process. Full article

Humanoid robots operating near humans require short protective reaction times in physical human–robot interaction (pHRI). Safety standards distinguish between quasi-static and transient contact. This paper quantifies the reaction timing of a compliant pneumatic artificial muscle (PAM) mechanism under controlled preload conditions. Measurements were performed at 10 N, 50 N, and 100 N preload using synchronised load-cell force, PAM pressure, actuator position, and force-sensitive resistor (FSR) signals. Reaction timing was evaluated relative to the FSR-defined contact onset, at which the controller issued the pressure-release command. The force trace reached its first post-contact peak within 15–20 ms after onset, while the pressure peak occurred within 5–15 ms. A 90% recovery of the post-contact force excursion was achieved within 40–50 ms, whereas the corresponding pressure excursion required 155–180 ms. These timing results quantify reaction latency in PAM-actuated humanoid joints and support multi-modal sensing for robust onset localisation and mitigation monitoring in both ISO/TS 15066 contact types. Full article

Integrated die-cast components reduce machining/assembly steps and improve mechanical dynamic characteristics, eliminating joint loosening/fracture risks after long-term use. However, the highly variable geometries and random spatial distributions of burrs, flash, parting lines, and risers in castings invalidate pre-programmed or teach-in robotic grinding methods. This paper reviews recent progress and future trends in robotic grinding, analyzing four core aspects: force control stability/adaptability (e.g., adaptive impedance control can reduce average force-tracking error to 0.38 N), trajectory planning/path generation (e.g., error-driven compensation can lower contour error by 34.2–55.1%), process parameter optimization, and challenges of sensing latency/quality evaluation (e.g., deep learning models achieve 97.64% accuracy in identifying abrasive belt wear states). The key enabling technologies are summarized, including active/passive compliant force control, model-/data-driven adaptive trajectory planning, intelligent process parameter optimization integrating physical mechanisms and data-driven approaches, and multi-modal state monitoring with online quality assessment. Representative applications (metal castings, aero-engine blades, thin-walled components, weld seams) are presented, and prospective research directions are proposed. This paper provides a comprehensive reference for theoretical research and engineering practice in this field. Full article

In the context of Industry 5.0, human–robot collaboration increasingly demands intuitive, safe, and sensorless interaction for tasks such as hand-guided teaching and concurrent manipulation. However, conventional admittance control systems are prone to instability due to abrupt changes in human arm stiffness and their reliance on accurate dynamic models. To address these challenges, this paper proposes a sensorless external force estimation and variable admittance control method that models robot dynamic uncertainties and interaction forces as normally distributed stochastic quantities. An improved particle swarm optimization algorithm is introduced to calibrate the variance parameters, enhancing estimation accuracy and robustness. Furthermore, an energy-based variable admittance control strategy is developed, which preserves system passivity by adaptively adjusting inertia and damping gains based on real-time energy variations. The proposed method was validated on a redundant robot platform. Experimental results show that the external force and torque estimation errors remain below 3 N and 3 N.m, respectively, with lower detection delays and errors than those of a first-order generalized momentum observer in collision detection. Variable admittance experiments demonstrate that the system maintains passivity and stable interaction even under sudden arm stiffness changes. The approach is well-suited for industrial applications requiring safe, sensorless, and compliant human–robot collaboration. Full article

With the continuous advancement of marine development, underwater operational tasks are becoming increasingly diverse and complex. Addressing the limitations of traditional methods and intelligent planning—which focus solely on acquiring task skills while separating grasp planning from force planning—this paper proposes a modeling approach integrating impedance control with deep reinforcement learning. Using a five-finger humanoid underwater dexterous hand as the grasping execution platform, this method achieves collaborative decision-making between grasp planning and force control for underwater dexterous hands. First, a modular underwater dexterous grasping scenario is established. Its kinematic model and inverse solution are analyzed, and the grasping problem is modeled as a Markov decision process. Second, based on the dexterous fingertip impedance control model for simulation, a grasping strategy learning method grounded in deep reinforcement learning is constructed to address the complex control challenges posed by the high degrees of freedom of the dexterous manipulator. Finally, the Proximal Policy Optimization (PPO) algorithm is employed for grasping strategy learning. An underwater dexterous grasping parallel training and testing environment is established using the Isaac Lab simulation platform to rapidly validate the learning method. Simulation results demonstrate the proposed method’s excellent dexterous compliant control performance and strong robustness to underwater variable environments: the PPO-based impedance control scheme reduces contact force variance by 56% compared to pure position control. The average maximum contact force is suppressed to 3.26 N, representing a 60.4% reduction compared to pure position control. This study achieves the organic integration of underwater hydrodynamic compensation, adaptive impedance control, and grasping strategy learning, providing a novel and effective solution for compliant grasping control of underwater dexterous manipulators. Full article

This study presents a unified mechanics-based framework for evaluating bonded composite patch repairs. Discrete fracture, fatigue, and adhesive responses are transformed into continuous master equations over the design space. Low-order polynomial surfaces model stress intensity and concentration responses, enabling continuous prediction of repair performance without repeated finite-element analyses. A fracture-based repair efficiency index is derived from the analytical master surface. This index quantifies the average reduction in crack-driving force across the domain. Combined with adhesive stiffness and strength, it defines an adhesive-based repair efficiency index (A-REI), providing a direct link between structural response and material properties. The results show that repair effectiveness is strongly influenced by both geometric severity and adhesive properties. Fatigue performance decreases significantly with increasing notch ratio in single-sided repairs. Double-sided configurations maintain consistently higher efficiency. Symmetric reinforcement more effectively reduces stress concentration, with improvements exceeding 40% at intermediate notch ratios. Adhesive selection is governed by stiffness and strength. Structural adhesives achieve significantly higher A-REI values, whereas compliant adhesives contribute negligibly. Overall, repair symmetry controls the magnitude of improvement, while adhesive properties determine performance ranking. This framework provides a clear, practical basis for design and material selection. Full article

The synchronous continuum robot (SCR) was developed to emulate biological structures, such as animal tails and elephant trunks, based on continuum robot principles. By synchronizing disk motions, the SCR generates biologically inspired continuous movements while maintaining precise trajectory control. However, its synchronization-based architecture limits adaptability during physical interaction due to rigid trajectory-following characteristics. To address this limitation, this paper proposes a sensorless variable admittance control (VAC)-based compliant motion generation framework for the SCR. A dynamic model-based sensorless disturbance observer is designed to estimate external torques without additional force sensors. To compensate for uncertainties inherent in the cable-driven transmission mechanism, an adaptive term is incorporated into the parameter identification process, improving disturbance estimation accuracy. Based on the estimated external torques, admittance parameters are adaptively modulated according to joint angles, angular velocities, and robot posture, enabling interaction-aware motion speed regulation. Furthermore, the proposed method simultaneously enforces constraints on both joint angles and angular velocities through the adaptive regulation of target positions and velocities, ensuring safe and physically feasible motion. Experimental results under various interaction scenarios demonstrate reliable contact-independent force estimation and effective compliant motion generation. The proposed framework provides an integrated solution for robust force estimation, adaptive compliance control, and simultaneous constraint enforcement in mechanically synchronized continuum robots. Full article

Understanding how geometry governs interfacial contact and material removal is central to designing efficient bioinspired surface systems. Gastropod radular teeth form natural arrays of microscale cutting elements optimized for repeated interaction with compliant and semi-rigid substrates, yet experimentally validated shape–performance relationships remain limited. Here, we isolate geometric effects on interfacial mechanics using stereolithography-printed biomimetic tooth arrays inspired by the taenioglossan radula of the hard-substrate grazer Spekia zonata. Two morphologically distinct tooth types (central and marginal) were systematically varied in cusp and stylus geometry (four variants each), while array configuration, material, and boundary conditions were kept constant. Tooth stiffness was quantified in bending tests as load-induced height reduction. Interfacial performance was assessed using a controlled pull-through assay in agarose substrates of two stiffness levels (0.4% and 0.8%), with continuous force recording and measurement of removed mass. Marginal-tooth geometries were stiffer and consistently removed more substrate than central variants. Although work increased substantially in stiffer gels, removal did not scale proportionally and declined for central teeth, revealing a decoupling between mechanical input and yield. Performance correlated with active engagement rather than work alone, indicating geometry-limited contact regimes. These findings establish geometry-controlled stiffness and engagement as key parameters for efficient abrasive interfaces. Full article

Interventional robots play a crucial role in surgical procedures, where accurate force measurement is essential for enhancing safety. Compliant mechanisms utilize material deformation to achieve millinewton-scale force output and millimeter-level displacement with high repeatability. Motivated by this, we propose a method for measuring the catheter force by integrating a compliant mechanism and a sensor. First, we designed an operating force detection module. It comprises a double-parallelogram structure with four elastic units, a catheter drive module, and a sensor. The sensor connects the compliant mechanism to the base. Second, stiffness and gravity compensation models were established and validated experimentally. Finally, we constructed an experimental platform to evaluate the force measurement accuracy, drive accuracy, and real-time detection capability. Experimental results demonstrate that the proposed method achieves a maximum detection error of 0.1482 N, an average error of 0.0096 N, a resolution of 0.01 N, and an average axial delivery error of 0.8287 mm. Additionally, a master–slave control framework was developed, along with a master controller that manipulates the slave robot to deliver the catheter within a vascular phantom, while simultaneously displaying real-time force information via the human–computer interaction interface. Full article

Six-dimensional force sensors are widely used in compliant robotic control and safe human–machine interactions due to their mature sensing mechanisms and high accuracy. However, conventional six-dimensional force sensors often suffer from complex structures, bulky size, and high manufacturing costs. To address these limitations, this paper proposes a compact and low-cost six-axis force sensor based on capacitive sensing. By employing a tailored arrangement of flexible sensing units, partial structural decoupling of force and torque in specific directions is achieved. A Physically Informed Neural Network (PINN) is further introduced to decouple the residual coupled signals. Experimental results demonstrate that the proposed method significantly improves decoupling accuracy, achieving force decoupling errors of 1.75%, 1.20%, and 1.31% for F_x, F_y, and F_z, respectively, and torque decoupling errors of 0.95%, 0.93%, and 0.97% for M_x, M_y, and M_z. The proposed sensor offers low-cost fabrication, compact integration, and high sensitivity, making it well suited for lightweight and high-precision sensing applications. Full article

This paper studies a MuJoCo-based locomotion framework that couples an adaptive-frequency central pattern generator (AFCO-CPG) with single rigid-body dynamics model predictive control (MPC) for the RENS Q1 quadruped with elastic parallel knee joints. AFCO-CPG combines multi-scale phase coordination, saturated phase correction, and load-gated feedback, while MPC supplies feasible ground-reaction forces and returns load cues to the timing layer. In MuJoCo, the controller achieves stable diagonal-trot speed tracking from 0.4 to 1.2 m/s and recovers from short external pushes. A matched elastic-versus-rigid timing sweep shows a favorable flat-ground parameter band around $\omega =1.8$ Hz, with a best-case cost-of-transport reduction of 12.83% for the elastic model under identical controller gains. A flat-to-slope ascent case further verifies that AFCO timing is modulated when load conditions change. Ablation across nine controller variants shows that multi-scale coordination is the dominant component, causing a 135% increase in phase error and a 536% increase in recovery time when removed. A reduced-order early/late-contact benchmark further confirms faster re-locking than diagonal-only and minimal variants. The results support the value of combining neural timing, predictive force optimization, and compliant-leg feedback in high-fidelity simulation, while hardware validation remains future work. Full article

The flexible upper-limb exoskeleton robot (exosuit) is composed of fabrics, soft actuators and compliant force-transmitting structures, which provides assistance or rehabilitation training for the shoulders, elbows, wrists and hands. By realizing human–robot collaboration, this kind of system has the advantages of comfort, light weight and portability, thus promoting motor function recovery and neural plasticity. This review establishes a classification and comparison framework for flexible upper-limb exoskeletons based on the actuation modalities and systematically summarizes the research progress under different actuation modalities. The relevant literature published from 2015 to 2025 was retrieved from the EI, IEEE Xplore, PubMed and Web of Science databases. After screening according to the preset inclusion and exclusion criteria, a total of 64 original research papers meeting the criteria were finally included for analysis. According to the actuation modalities, the flexible upper-limb exoskeleton robot is classified, and all kinds of systems are summarized and compared. Motor–cable/tendon actuation and pneumatic/hydraulic actuation have advanced substantially and are approaching technical maturity for flexible upper-limb exoskeletons. Meanwhile, designs based on passive/hybrid mechanisms (e.g., elastic energy storage elements and clutches) and new intelligent material actuations are showing a diversified development trend. In the future, the development is expected to further focus on lightweight and compliance, and by integrating multimodal sensing and feedback control, motion intention recognition and human–robot interaction theories, actuation systems will be developed towards modularization, intelligence and high-power density, in order to achieve more comfortable, lighter and more effective flexible upper-limb exoskeleton systems. Full article

Flexible and safe object handling in modern industrial environments increasingly relies on mobile robotic systems capable of both dexterous manipulation and adaptive motion. However, when wheeled mobile manipulators (WMMs) operate under heavy or dynamically varying loads, challenges arise in maintaining sufficient force exertion capability and achieving stable coordination, particularly during cooperative transportation. In this paper, we present a unified framework to address these challenges with three main contributions. A quadratic-programming-based redundancy resolution scheme incorporating a load-capacity maximization metric is developed to explicitly enhance the force exertion capability of the system under heavy loads. A variable-admittance cooperative control strategy for dual-WMM transport is proposed to ensure synchronized motion and adaptive force regulation during collaborative manipulation. In addition, a unified framework that integrates configuration optimization with compliant cooperative control is established, enabling strict constraint enforcement, improved load capacity, and robust coordination between the two WMMs. Extensive simulations demonstrate the effectiveness of the proposed methods in improving load-handling performance and ensuring coordinated, compliant cooperative manipulation. Full article

Stick-slip actuators have emerged as a promising solution for precision positioning, which can help attain a nanometer-scale resolution and large stroke size. This review summarizes recent advances in the design, modeling, and performance enhancement of non-resonant stick-slip actuators systematically. Three fundamental actuation principles, including conventional, parasitic, and hybrid types, are reported, which highlight their respective mechanisms for stepwise motion generation. We examine the development of linear and rotational actuators and reveal the function of compliant amplification mechanisms, asymmetric stiffness configurations, and bio-inspired architectures in improving step consistency, load capacity, and compactness. We also examine the effects of step displacement optimization, active preload control, and advanced dynamic modeling on motion precision. We suggest that future development prioritize enhancing driving force, suppressing backward motion, improving dynamic response, and ensuring long-term reliability. Full article