This paper presents a control method for a cable-suspended aerial manipulator performing high-altitude contact tasks. The target tasks include polishing and wiping on planar and curved surfaces, in which the end-effector must maintain a desired contact force while the suspended aerial manipulator remains stable against contact-induced disturbances. The proposed framework consists of a winch-based attitude and altitude controller, a propulsion controller for horizontal position and yaw stabilization, and a task-space manipulator controller with admittance-based force regulation. The winch system regulates the roll, pitch, and altitude of the platform by adjusting the cable lengths. The propulsion system counteracts horizontal disturbances through damping control, position regulation, disturbance compensation, and constrained control allocation. The manipulator generates a reference end-effector trajectory from the contact-force error along the surface-normal direction and tracks this reference using closed-loop inverse kinematics. Simulation results for side-plane, bottom-plane, side-curved, and bottom-curved contact tasks demonstrate that the proposed method maintains the desired contact force while suppressing platform displacement during contact.
Robotic grasping in unstructured environments demands closed-loop feedback that goes beyond conventional fixed open-loop force control. Vision sensors suffer from occlusion at the instant of contact, whereas wrist-mounted force/ torque sensors cannot resolve local shear stress distributions or incipient slip at multi-contact interfaces. Tactile sensors bridge this gap by mapping high-dimensional contact physics directly and in real time. This paper surveys grasp intelligence technology within a Perception–State Estimation–Action framework. Specifically, it reviews optical and arraytype tactile sensors; slip detection algorithms, ranging from physics-based local deformation analysis to deep spatiotemporal networks; and active closed-loop force regulation, including diffusion-policy-based reactive control. Applications in precision semiconductor and electronics assembly are then discussed. Finally, outstanding challenges in mechanical durability, ultra-low-latency data processing, intelligent tactile skin, and multi-modal Vision-Language-Action integration are identified as priorities for future research.
To support die-motion design for double-sided symmetric forming of tubular stabilizer bars, this study developed an integrated finite-element (FE)–artificial neural network (ANN) framework for predicting springback and cross-sectional deformation. An R45 Abaqus model was calibrated against tensile responses from three circumferential positions. Free-end simulations established a neutral material inflow of 7.32 mm per 10° of bending. In the fixed-end database analyses, the bending die and support block were translated together by the prescribed axial displacement. Twelve commanded angles and five die-feed offsets generated a 60-case database. After min-max normalization, the 48 development cases underwent five-fold cross-validation, and the 12 holdout cases were reserved for one-time final evaluation. Across the four responses, mean cross-validation R² values ranged from 0.849 to 0.967, and holdout R² values from 0.913 to 0.976. The 2-20-20-4 ANN was then retrained using all 60 cases. R45 fixed-end FE results under the neutral die-feed condition yielded a springback RMSE of 0.275° and a MAPE of 6.29%. Over 10–120°, the maximum relative deviations were 3.52% (minimum outer diameter), 3.65% (minimum wall thickness), and 3.10% (maximum wall thickness). The final surrogate model supports rapid response estimation and angle compensation for new input combinations within the FE design space.
Emotional engagement is a critical factor in audiovisual entertainment environments such as movies, performances, and immersive exhibitions. This study developed a voice-coil-based seat-integrated vibrotactile system and investigated its effects on users’ affective experiences during audiovisual content consumption. Unlike conventional wearable haptic devices, the proposed system provides vibrotactile feedback through the seat structure without requiring equipment, offering a practical configuration for public audience environments. A total of 127 participants were randomly assigned to either an audiovisualonly condition (AV) or an audiovisual condition with synchronized seat vibrotactile feedback (AVH). Participants viewed 50 emotion-inducing video clips categorized into neutral, fun, sadness, anger, and fear. Subjective responses were collected using self-assessment questionnaires measuring valence, arousal, dominance, liking, and emotion intensity. The data were analyzed using linear mixed-effects models (LMMs) to account for repeated measurements and variability among participants and stimuli. The results showed that the AVH condition was associated with significantly higher arousal and lower dominance scores than the AV condition. In addition, sadness and fear intensities increased significantly under vibrotactile feedback. Significant interaction effects were observed for valence in sadness, liking in fun and sadness, and anger intensity in fear, indicating that seat-integrated vibrotactile feedback can modulate affective experiences depending on audiovisual content.
This paper describes an AI-based method for detecting and measuring cracks in the lower mold of a press. During continuous press operation, cracks can form in the lower mold and lead to product defects, which makes manual inspection by operators necessary. In this study, images of the lower mold were captured using a mechanical system developed in our previous study, in which an endoscopic camera is installed at the center of the upper mold. An AI program was then developed using YOLOv8. Images of cracked lower molds were captured at various camera heights, and the crack regions in the captured images were annotated with bounding boxes to train the AI model. Using the trained model, the AI program determines the presence of cracks in the lower mold and calculates the actual size represented by each pixel according to the camera height, thereby enabling the crack dimensions to be measured. The developed program can reduce the burden of manual inspection and provide quantitative information for determining maintenance schedules, thus contributing to the prevention of product defects and the stable operation of press processes.
