Cutting the Cord: System Architecture for Low-Cost, GPU-Accelerated Bimanual Mobile Manipulation
This provides a low-cost alternative for research and education in robotics and robot learning, though it is incremental as it builds on existing open-source platforms.
The paper tackled the problem of high-cost bimanual mobile manipulation by developing a low-cost, GPU-accelerated robot with integrated onboard compute for under $1300, enabling teleoperation, autonomous SLAM navigation, and vision-based manipulation without external dependencies.
We present a bimanual mobile manipulator built on the open-source XLeRobot with integrated onboard compute for less than \$1300. Key contributions include: (1) optimized mechanical design maximizing stiffness-to-weight ratio, (2) a Tri-Bus power topology isolating compute from motor-induced voltage transients, and (3) embedded autonomy using NVIDIA Jetson Orin Nano for untethered operation. The platform enables teleoperation, autonomous SLAM navigation, and vision-based manipulation without external dependencies, providing a low-cost alternative for research and education in robotics and robot learning.