BiPreManip: Learning Affordance-Based Bimanual Preparatory Manipulation through Anticipatory Collaboration

2026-03-23

AI Summary

This work addresses the challenge of manipulating everyday objects whose shapes or poses hinder direct grasping or interaction. To this end, the authors propose a vision-based, affordance-driven bimanual coordination framework that anticipates functional actions on target objects and guides one arm to perform preparatory manipulations, thereby enabling long-horizon, asymmetric dual-arm collaboration. The core innovation lies in an affordance-centric representation that integrates spatial relationship prediction with long-horizon action planning, facilitating proactive coordination and cross-category generalization. Experimental results demonstrate that the proposed method significantly improves task success rates and generalization across object categories in both simulated and real-world environments, outperforming existing baselines.

Technology Category

• Intelligent Robots: Manipulation
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Multiagent Systems: Coordination and Collaboration

Application Category

• Economics, Online Markets and Human Computation: The sharing economy
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

Many everyday objects are difficult to directly grasp (e.g., a flat iPad) or manipulate functionally (e.g., opening the cap of a pen lying on a desk). Such tasks require sequential, asymmetric coordination between two arms, where one arm performs preparatory manipulation that enables the other's goal-directed action - for instance, pushing the iPad to the table's edge before picking it up, or lifting the pen body to allow the other hand to remove its cap. In this work, we introduce Collaborative Preparatory Manipulation, a class of bimanual manipulation tasks that demand understanding object semantics and geometry, anticipating spatial relationships, and planning long-horizon coordinated actions between the two arms. To tackle this challenge, we propose a visual affordance-based framework that first envisions the final goal-directed action and then guides one arm to perform a sequence of preparatory manipulations that facilitate the other arm's subsequent operation. This affordance-centric representation enables anticipatory inter-arm reasoning and coordination, generalizing effectively across various objects spanning diverse categories. Extensive experiments in both simulation and the real world demonstrate that our approach substantially improves task success rates and generalization compared to competitive baselines.

Problem

• bimanual manipulation
• preparatory manipulation
• affordance
• anticipatory collaboration
• object semantics

Innovation

• bimanual manipulation
• affordance-based reasoning
• preparatory manipulation
• anticipatory collaboration
• visual affordance