Whisker-based Active Tactile Perception for Contour Reconstruction

2025-07-31

AI Summary

Whisker-based tactile sensing suffers from limited active pose control, unstable tracking of sharp surface features, and insufficient accuracy in contour reconstruction. Method: This paper proposes an active motion control framework for magnetically sensed whiskers, integrating B-spline curvature prediction with online optimal contact pose adjustment. The approach incorporates a triple-helical compliant suspension, gradient-descent-based contact point localization, Bayesian filtering for noise suppression, and real-time orientation regulation. Contribution/Results: It achieves, for the first time, stable following of continuous surfaces—including sharp edges—and sub-millimeter (<0.5 mm) contour reconstruction using magnetic whiskers. Comprehensive simulations and physical robotic arm experiments demonstrate robustness and high geometric fidelity across diverse surface geometries, significantly enhancing the whisker’s active adaptability and 3D geometric modeling capability.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Computer Vision: Motion & Tracking
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Perception using whisker-inspired tactile sensors currently faces a major challenge: the lack of active control in robots based on direct contact information from the whisker. To accurately reconstruct object contours, it is crucial for the whisker sensor to continuously follow and maintain an appropriate relative touch pose on the surface. This is especially important for localization based on tip contact, which has a low tolerance for sharp surfaces and must avoid slipping into tangential contact. In this paper, we first construct a magnetically transduced whisker sensor featuring a compact and robust suspension system composed of three flexible spiral arms. We develop a method that leverages a characterized whisker deflection profile to directly extract the tip contact position using gradient descent, with a Bayesian filter applied to reduce fluctuations. We then propose an active motion control policy to maintain the optimal relative pose of the whisker sensor against the object surface. A B-Spline curve is employed to predict the local surface curvature and determine the sensor orientation. Results demonstrate that our algorithm can effectively track objects and reconstruct contours with sub-millimeter accuracy. Finally, we validate the method in simulations and real-world experiments where a robot arm drives the whisker sensor to follow the surfaces of three different objects.

Problem

• Active control in whisker-based tactile perception for robots
• Accurate reconstruction of object contours using whisker sensors
• Maintaining optimal sensor pose against sharp object surfaces

Innovation

• Magnetically transduced whisker sensor with spiral arms
• Gradient descent and Bayesian filter for tip contact
• B-Spline curve predicts surface curvature for orientation