Affordance-Guided Enveloping Grasp Demonstration Toward Non-destructive Disassembly of Pinch-Infeasible Mating Parts

2026-03-22

AI Summary

This work addresses the challenge of robotic disassembly of complex mating parts, where conventional pinch grasps are infeasible and severe visual occlusion combined with geometric constraints renders 2D-image-based teaching inadequate for effective enveloping grasps. To overcome this, the authors propose an affordance-guided teleoperation approach that leverages physics-based simulation to pre-generate multi-finger enveloping grasp candidates. An affordance template is introduced to visualize grasp quality through color gradients in augmented reality, enabling human operators to efficiently select non-destructive grasping strategies even under highly constrained conditions. Simulations demonstrate the method’s generalizability across diverse components, while real-robot experiments confirm that operators can accurately teach practical, disassembly-ready grasps using this framework.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Low Level & Physics-based Vision
• Planning, Routing, and Scheduling: Mixed Discrete/Continuous Planning

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

Robotic disassembly of complex mating components often renders pinch grasping infeasible, necessitating multi-fingered enveloping grasps. However, visual occlusions and geometric constraints complicate teaching appropriate grasp motions when relying solely on 2D camera feeds. To address this, we propose an affordance-guided teleoperation method that pre-generates enveloping grasp candidates via physics simulation. These Affordance Templates (ATs) are visualized with a color gradient reflecting grasp quality to augment operator perception. Simulations demonstrate the method's generality across various components. Real-robot experiments validate that AT-based visual augmentation enables operators to effectively select and teach enveloping grasp strategies for real-world disassembly, even under severe visual and geometric constraints.

Problem

• enveloping grasp
• non-destructive disassembly
• visual occlusion
• geometric constraints
• pinch-infeasible

Innovation

• affordance-guided teleoperation
• enveloping grasp
• affordance templates
• non-destructive disassembly
• physics simulation