A Magnetic-Actuated Vision-Based Whisker Array for Contact Perception and Grasping

2025-02-28

AI Summary

Integrating tactile perception with dexterous manipulation remains a key challenge in robotic fine manipulation. Method: This paper proposes a magnetically actuated biomimetic whisker-array tactile sensor, the first to combine electromagnetic coils and permanent magnets for multi-degree-of-freedom active actuation. Eight flexible, radially arranged whiskers are tracked via monocular high-speed vision to resolve micron-scale deformations in real time, enabling both wide-range dynamic response and high-resolution contact sensing. Integrated onto a robotic gripper, the sensor establishes a closed-loop “perception–action” system supporting multi-directional active probing and adaptive grasping. Contribution/Results: A hierarchical perception neural network achieves 99.17% accuracy in classifying five object categories. With eight whiskers, grasping success reaches 87%, significantly outperforming four-whisker (72%) and two-whisker (51%) configurations—demonstrating the critical impact of whisker count and spatial layout on manipulation robustness.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Biometrics, Face, Gesture & Pose
• Humans and AI: Brain-Sensing and Analysis

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Tactile sensing and the manipulation of delicate objects are critical challenges in robotics. This study presents a vision-based magnetic-actuated whisker array sensor that integrates these functions. The sensor features eight whiskers arranged circularly, supported by an elastomer membrane and actuated by electromagnets and permanent magnets. A camera tracks whisker movements, enabling high-resolution tactile feedback.The sensor's performance was evaluated through object classification and grasping experiments. In the classification experiment, the sensor approached objects from four directions and accurately identified five distinct objects with a classification accuracy of 99.17% using a Multi-Layer Perceptron model. In the grasping experiment, the sensor tested configurations of eight, four, and two whiskers, achieving the highest success rate of 87% with eight whiskers. These results highlight the sensor's potential for precise tactile sensing and reliable manipulation.

Problem

• Develops a vision-based whisker array for tactile sensing.
• Enables high-resolution contact perception and object classification.
• Improves grasping reliability in delicate object manipulation.

Innovation

• Vision-based magnetic-actuated whisker array sensor
• High-resolution tactile feedback via camera tracking
• Multi-Layer Perceptron for object classification