The safe and reliable manipulation of fragile objects remains a central challenge in soft robotics, particularly for cable-driven grippers in which actuation forces are indirectly transmitted through highly compliant structures. For automation and control purposes, establishing a link between the actuation variable—cable tension—and a physically meaningful grasp metric, such as contact pressure, is essential for defining operational safety limits. This work investigates the mechanical behaviour of a SpiRob-type soft gripper, with a specific focus on the characterization of contact pressure distribution under actuation.
Rather than relying exclusively on detailed material calibration, this study explores modelling frameworks aimed at estimating the pressure generated at the gripper–object interface. The proposed approach analyses the structural response of the soft actuator to relate applied cable tension to the resulting contact pressure for objects with different geometries. Both theoretical and computational perspectives are employed to establish a robust mapping between actuation input and grasping performance. The resulting characterization enables the definition of pressure-based safety regions that are directly relevant to gripper design and low-level control strategies. By providing a practical method for estimating contact stress without the need for extensive experimental calibration, this work contributes to the development of safer, more predictable, and more controllable cable-driven soft robotic manipulation systems.

This paper presents a duty-cycle-driven design and optimization methodology for an Interior Permanent Magnet Synchronous Motor (IPMSM) intended for off-highway vehicle applications, based on real-world maneuver analysis. Off-highway machines such as wheel loaders operate under highly dynamic and repetitive load conditions that significantly differ from standardized road vehicle drive cycles. To accurately capture these operating characteristics, representative wheel-loader duty cycles are analyzed to extract realistic torque–speed–time operating envelopes. These envelopes are subsequently used to define application-specific performance targets and constraints, ensuring proper motor sizing and electromagnetic design aligned with real operating conditions.

A preliminary IPMSM design is first established using analytical sizing rules and electromagnetic design guidelines. This baseline design is then validated through high-fidelity finite-element analysis (FEA) using ANSYS Motor-CAD, enabling detailed evaluation of electromagnetic performance, losses, and efficiency under both steady-state and transient conditions. To systematically improve the motor design, a sensitivity analysis based on Design of Experiments (DoE) is conducted using ANSYS optiSLang. This step identifies the most influential geometric and magnetic design parameters affecting key performance indicators such as torque capability, efficiency, torque ripple, cogging torque, and motor mass.

Building on the sensitivity analysis results, a surrogate-assisted multi-objective optimization employing Particle Swarm Optimization (PSO) is performed. The optimization aims to enhance efficiency, reduce torque ripple and cogging torque, and minimize motor mass while satisfying strict electromagnetic, mechanical, and application-driven constraints. Comparative electromagnetic evaluation between preliminary and optimized designs demonstrates significant improvements in torque smoothness, harmonic content, and efficiency, confirming the effectiveness of the proposed optimization framework for off-highway electric powertrain applications.

Introduction: Global electricity demand has increased significantly in recent decades, driven primarily by the growth of industrial and commercial activities. Electric motor systems account for more than 53% of the world's electricity consumption, with a strong predominance of the industrial sector. Despite the widespread use of three-phase induction motors, limitations such as reduced performance under partial loads, absence of direct speed control, high starting currents, and construction constraints have encouraged the search for technological alternatives. Regulatory requirements for energy efficiency, namely IEC 61800-9-2:2023, reinforce this need. In this context, SRM stands out as a promising solution, offering high power density and less dependence on critical materials. Thus, this work aims to analyze the energy performance of a switched reluctance motor and evaluate the applicability of the methods defined in IEC 61800-9-2:2023.

Methods: In this work, an experimental study was carried out on an SRM motor driven by a TURNtide converter. The losses of the motor, the Complete Drive Module (CDM) and the Power Drive System (PDS) are measured for two test methods: the method based on the IEC 61800-9-2:2023 standard, and a test method based on thermal stabilization. The motor drive is tested at the standardized operating points defined in the IEC 61800-9-2:2023 standard.

Results: The results indicate that the highest percentual variations occur in conditions far from the nominal regime, especially at low load torque and low speed, while the agreement between the methods is high at the operating points close to the nominal load.

Conclusion: The results indicate that the test method defined in IEC 61800-9-2 provides consistent loss estimations under nominal regimes but has limitations under partial load conditions. It is recommended to (i) integrate thermal stabilization at the standardized points and (ii) adapt the standard to the specificities of switched reluctance motor drives.

Quadruped robots are increasingly used as experimental platforms for studying locomotion and control strategies in robotics. However, developing and validating control approaches often requires low-level programming and fragmented vendor tooling, which can hinder rapid experimentation and reduce repeatability. This work presents a MATLAB-based framework that enables systematic experimentation on a physical quadruped robot through a wireless communication layer while leveraging the robot’s existing onboard motion stack. Instead of implementing gaits from scratch, the framework provides MATLAB-side access to baseline locomotion primitives already available on the platform (e.g., forward, stop, and turning commands), enabling the controlled experimentation and parameterized testing of locomotion and actuation behaviors, and complements them with low-level actuator access for controlled posture and joint/servo-level tests under conservative bounds and safety-oriented rate limiting. On the sensing side, the framework consolidates sensor feedback streams for experimental observation and logging, including actuator state and onboard sensing data used during experiments, depending on the available hardware configuration. The result is a simple closed-loop workflow in which MATLAB issues commands, the robot executes them using existing motion routines, and MATLAB captures synchronized feedback for repeatable trials and dataset generation. Experimental feasibility is demonstrated through experiments on a physical quadruped robot, including locomotion and posture command execution with real-time monitoring. The proposed framework lowers the barrier to structured experimentation and provides a practical foundation for future extensions, including adaptive control and learning-based methods for legged robots.

Introduction:
Six-phase induction machines represent an evolution of conventional three-phase systems, offering enhanced reliability, efficiency, and fault tolerance. The additional degrees of freedom introduced by the six-phase configuration result in multiple orthogonal subspaces, namely the α–β plane responsible for torque production and the x–y subspace, which does not contribute to torque and is mainly associated with copper losses and harmonic components.

Methods:
This work proposes an enhanced space vector pulse width modulation (SVPWM) strategy specifically developed for asymmetrical six-phase induction machines. The proposed approach enables accurate synthesis of the reference voltage vector in the α–β plane while ensuring zero average voltage injection in the x–y subspace for any angular position. Unlike virtual-vector-based modulation techniques reported in the literature, the proposed strategy is not restricted to specific sectors or angular regions and is applicable over the entire range of reference voltage vector magnitudes.

Results:
The effectiveness of the proposed SVPWM strategy was first assessed through simulation and subsequently validated through experimental tests. The results demonstrate a significant reduction in stator current total harmonic distortion (THD) and a noticeable decrease in torque ripple when compared with conventional SVPWM approaches.

Conclusions:
By actively suppressing voltage components in the x–y subspace while preserving the desired voltage synthesis in the α–β plane, the proposed SVPWM strategy improves current quality and torque smoothness in six-phase induction machines. These features make the approach suitable for high-performance and high-reliability multiphase drive applications.

Modern robotic systems require actuators capable of delivering high precision and reliable performance across diverse tasks. In this context, the BEAR (Belt Elastic Actuator for Robotics), developed by Smile.Tech, is a belt-driven elastic robotic actuator, conceived as an active joint suitable for multiple robotic architectures and applications. Its elastic transmission provides reduced mechanical backlash compared to traditional rigid-gear solutions, ensuring consistent motion. However, the BEAR is currently operated through trial-and-error using position feedback from two encoders—one on the motor and one on the output shaft— whereby performance depends on empirical tuning, reducing reliability in more dynamic operating regimes. This paper presents the identification of the BEAR actuator, producing models that describe its dynamic behaviour. These models make it possible to replace empirical tuning, enabling predictive simulation, supporting advanced control methods, and allowing systematic use of the actuator’s elastic properties. The proposed study relies on dedicated experimental input–output data to characterise the dynamic behaviour of the BEAR actuator under relevant operating conditions. These data are used in grey-box modelling, combining the physical knowledge of the system and data-driven parameter estimation. Prior to application on the BEAR, the approach is validated on progressively complex systems, allowing refinement of the identification procedure and ensuring the reliability of the resulting models. This study aims to develop a consistent model of the BEAR actuator, establishing a quantitative foundation for subsequent analysis and control. By enabling model-based operation and control design, this work seeks to support improved precision, predictability, and reliability in robotic tasks, with potential implications for multifunctional elastic joint applications.

Friction in passive joints plays a critical role in the dynamic behavior, accuracy, repeatability, and energetic efficiency of parallel robotic systems, particularly in Delta-type architectures. These effects are especially pronounced in low-cost robotic platforms, where manufacturing tolerances, material choices, and joint surface quality can significantly amplify friction-related phenomena. This paper presents a parametric analysis of joint friction effects on the dynamic and kinematic performance of a low-cost Delta parallel robot, based on an existing multibody model developed in the MATLAB Simscape Multibody environment. The proposed methodology exploits the native joint friction modeling capabilities of Simscape Multibody, enabling the systematic introduction and comparison of different friction formulations within the robot’s passive joints. Several friction models are considered, ranging from classical Coulomb and viscous formulations to nonlinear models capable of capturing velocity-dependent effects. The influence of friction parameter variations is evaluated in terms of positioning accuracy, repeatability, dynamic response, and mechanical energy consumption along representative motion trajectories. Particular attention is given to the trade-off between increased energy demand due to friction and its stabilizing effect on the system’s dynamic behavior. The results provide insight into how friction modeling choices and parameter values affect the overall performance of low-cost Delta robots, supporting informed decision-making during mechanical design and simulation-based analysis. The proposed framework also establishes a foundation for future extensions toward vibration analysis, wear modeling, and friction-aware control strategies.

This work mainly investigates the performance of two current control strategies for grid-connected inverters: the first operates in a synchronous reference frame and uses proportional–integral (PI) controllers, while the second control solution is implemented in a stationary reference frame and makes use of a proportional–resonant (PR) controller. The PI controllers are widely adopted due to their limited dependence on an accurate plant model, whereas the PR controllers are particularly suited for sinusoidal reference tracking. The comparison of the two control strategies has been realized considering different performance metrics, such as the ì command tracking capability, load disturbance rejection, and noise sensitivity. The PI controller operates on constant quantities and, therefore, requires a synchronous reference frame transformation and decoupling terms to compensate for the effects of the plant. Variations in system parameters may compromise its stability. In contrast, the PR controller does not require reference frame transformations or decoupling terms, but it achieves optimal performance only at the resonant frequency, corresponding, in our case, to the grid frequency. Stability analysis for both control strategies is carried out by including the output LCL filter in the current control loop, resulting in resonance peaks in the transfer functions. Simulation results show that the PI controller offers a favorable trade-off between robustness and dynamic performance when the grid angle is accurately provided by the phase-locked loop. Otherwise, the PR controller demonstrates superior performance due to its independence from grid angle estimation.

Recent advancements in electromagnetic machine design have driven significant interest in coreless topologies employing planar coils, owing to their lightweight structure and manufacturing advantages. This study presents a comparative analysis of four planar coil variants integrated into a Dual-Rotor Single-Stator Generator (SSDR), aiming to evaluate and enhance electromagnetic performance. The investigated coil geometries include Planar Square Coil (PSC), Planar Rhomboidal Coil (PRHC), Planar Trapezoidal Coil (PTC), and Planar Rectangular Coil (PRC). Finite element analysis (FEA) was employed to assess critical performance metrics such as coil flux density, magnetic field distribution, and flux linkage for each configuration. The results indicate that the PTC demonstrates superior electromagnetic characteristics, exhibiting an optimal flux distribution profile and high flux linkage. Among all tested variants, the PTC outperformed the PSC, PRHC, and PRC by 2.5%, 2.2%, and 1.75%, respectively, in overall electromagnetic performance. The PRC followed closely behind in terms of flux linkage but showed relatively less uniform field distribution. This comparative study underscores the potential of the trapezoidal planar coil for use in lightweight, high-efficiency SSDR generators. The findings provide valuable insights for optimizing planar winding designs in next-generation coreless generator applications. Future work will focus on experimental validation and thermal performance analysis of the proposed configurations.

In this study, two Brushless Direct Current (BLDC) motor topologies—a dual-stator single-rotor axial-flux (DSSR-AF) BLDC motor and a radial-flux inner-rotor (RF inrunner) BLDC motor—are comparatively investigated under identical rated power (10 kW) and equivalent electrical and magnetic material properties. The two motor topologies are designed with distinct magnetic flux paths and structural architectures. The axial-flux motor employs an axial-flux path combined with a dual-stator configuration, whereas the radial-lux motor is based on a conventional inner-rotor structure with a radial-flux path.

During the preliminary design stage, analytical sizing methods are utilized, while the final electromagnetic performance evaluations are conducted using ANSYS RMxprt-assisted modeling and transient finite element analysis (FEA) performed in ANSYS Maxwell 2D. The comparative assessment includes key electromagnetic performance metrics such as average torque, torque ripple, magnetic flux density, efficiency, copper and iron losses, total losses, and torque and power density.

The simulation results indicate that the RF-BLDC motor achieves an efficiency approximately 4.71% higher than that of the DSSR-AF-BLDC motor. The average torque values are 24.6 Nm for the RF-BLDC motor and 13.7 Nm for the DSSR-AF-BLDC motor. The maximum air-gap magnetic flux densities are observed to be 0.48 T and 0.69 T, respectively. These findings demonstrate that the DSSR-AF-BLDC motor offers superior performance in terms of power and torque density, whereas the RF-BLDC motor exhibits an advantage in efficiency.

Although comparative studies on axial- and radial-flux BLDC motor topologies exist in the literature, direct comparisons of DSSR-AF-BLDC motors and conventional RF inrunner BLDC motors at the same power level under fully equivalent electromagnetic and material conditions remain limited. This study provides an original contribution by clearly revealing the efficiency–power density and torque-orientated performance trade-off for BLDC motor topology selection in electric unmanned aerial and ground vehicle applications at the 10 kW power level.