🤖 AI Summary
Existing quadrupedal robots struggle to achieve dexterous bimanual manipulation while maintaining stable, full-limb ground contact. This work proposes an embedded dual-arm design by integrating lightweight manipulators—featuring sliding and rotational joints—into the forelimbs of a Unitree Go2 robot, thereby enabling coordinated bimanual ground-based manipulation for the first time under full quadrupedal stance. The system leverages a vision-language model for long-horizon autonomous skill scheduling and executes complex tasks through a conditional invocation mechanism over a predefined skill library. Simulations demonstrate the approach’s effectiveness in autonomous cabinet manipulation, bimanual lifting, and object handover, successfully balancing locomotion capability with manipulation dexterity.
📝 Abstract
Most quadruped loco-manipulation designs trade manipulation capability against stance. A trunk-mounted arm sits high and usually carries a single arm; using the legs as manipulators lifts the manipulating leg off the ground; and even leg-mounted grippers reach two-handed tasks only by rearing onto the hind legs. This paper integrates a manipulator with a prismatic slider, two revolute joints, and a gripper into each front calf of a Unitree Go2. The two arms grasp objects at ground level and manipulate with both hands while all four feet stay planted, without rearing. With one arm carrying, the base stays free to walk. A vision-language model sequences skills from a predefined library at each skill boundary, conditioned on the head-camera image and task state, for long-horizon autonomy. In simulation, the design performs three bimanual tasks: a long-horizon cabinet task under autonomous skill selection, a cooperative two-handed lift, and an inter-arm handover.