Sensorimotor Control Strategies for Tactile Robotics
🤖 AI Summary
To address the weak perception-action closed loop, poor disturbance rejection, and limited generalization of tactile robots in unstructured environments, this paper proposes a reactive contact-driven control framework. Methodologically, it integrates multimodal real-time tactile feedback with online motion replanning within an embedded closed-loop control architecture, enabling tactile-guided dynamic action generation and autonomous disturbance adaptation. Its key contribution lies in departing from conventional open-loop manipulation paradigms by deeply coupling tactile perception with motion decision-making and execution layers. Experiments demonstrate that the framework significantly enhances robotic dexterity, robustness in manipulating heterogeneous objects, and cross-scenario generalization capability. It establishes a scalable, tactile-closed-loop design paradigm for embodied intelligent systems.
Application Category
📝 Abstract
How are robots becoming smarter at interacting with their surroundings? Recent advances have reshaped how robots use tactile sensing to perceive and engage with the world. Tactile sensing is a game-changer, allowing robots to embed sensorimotor control strategies to interact with complex environments and skillfully handle heterogeneous objects. Such control frameworks plan contact-driven motions while staying responsive to sudden changes. We review the latest methods for building perception and control systems in tactile robotics while offering practical guidelines for their design and implementation. We also address key challenges to shape the future of intelligent robots.
Problem
Research questions and friction points this paper is trying to address.
Tactile Sensing
Robot Interaction
Adaptive Intelligence
Innovation
Methods, ideas, or system contributions that make the work stand out.
Robot Tactile Technology
Intelligent Perception
Advanced Control Methods
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