ROLGJun 11, 2025

Scoop-and-Toss: Dynamic Object Collection for Quadrupedal Systems

arXiv:2506.09406v1
Originality Incremental advance
AI Analysis

This work addresses the challenge of dynamic object collection for quadruped robots, expanding their capabilities beyond locomotion into loco-manipulation, though it appears incremental as it builds on existing leg-based manipulation research.

The paper tackles the problem of enabling quadruped robots to collect objects without additional actuators by attaching a simple scoop-like add-on to one leg, allowing them to scoop and toss objects into a collection tray on their back, with a hierarchical policy structure demonstrating effective dynamic manipulation.

Quadruped robots have made significant advances in locomotion, extending their capabilities from controlled environments to real-world applications. Beyond movement, recent work has explored loco-manipulation using the legs to perform tasks such as pressing buttons or opening doors. While these efforts demonstrate the feasibility of leg-based manipulation, most have focused on relatively static tasks. In this work, we propose a framework that enables quadruped robots to collect objects without additional actuators by leveraging the agility of their legs. By attaching a simple scoop-like add-on to one leg, the robot can scoop objects and toss them into a collection tray mounted on its back. Our method employs a hierarchical policy structure comprising two expert policies-one for scooping and tossing, and one for approaching object positions-and a meta-policy that dynamically switches between them. The expert policies are trained separately, followed by meta-policy training for coordinated multi-object collection. This approach demonstrates how quadruped legs can be effectively utilized for dynamic object manipulation, expanding their role beyond locomotion.

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