Low-Cost Mobile Bimanual Manipulation for Long-Horizon Toilet Cleaning

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Article Summary

Vision-Language-Action (VLA) models have shown promising capabilities for robot manipulation, but their performance on accessible mobile bimanual platforms remains underexplored. We present a low-cost and reproducible mobile bimanual platform integrating two LeRobot SO-101 manipulators with a TurtleBot 4 and a LeRobot-ROS 2 software stack. Using long-horizon toilet cleaning as a case study, we collect 250 real-world demonstrations and evaluate $π_0$, $π_{0.5}$, SmolVLA, and GR00T under the same embodiment and task conditions. We further evaluate variants using SARM-derived task-progress signals and short-term MEM observation history. Among the evaluated models, $π_0$ performs best, achieving 60% strict and 70% relaxed autonomous success, increasing to 90% with limited human intervention. In contrast, the evaluated progress- and memory-augmented variants do not improve their corresponding baselines. Our results demonstrate the feasibility of long-horizon mobile bimanual manipulation on accessible hardware while highlighting remaining challenges in reliable VLA deployment. Project website: https://so101-turtlebot4.github.io/mobile-bimanual-cleaning/

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