Mobile Aloha is a whole-body remote operation data collection system developed by Zipeng Fu, Tony Z. Zhao, and Chelsea Finn from Stanford University. Its hardware is based on 2 robotic arms (ViperX 300), equipped with 2 wrist cameras and 1 top camera, and a mobile base from AgileX Robotics Tracer differential motion robot, etc. Data collected using Mobile ALOHA, combined with supervised behavior cloning and joint training with existing static ALOHA datasets, can improve the performance of mobile manipulation tasks. With 50 demonstrations for each task, joint training can increase the success rate by 90%. Mobile ALOHA can autonomously perform complex mobile manipulation tasks such as cooking and opening doors. Special thanks to the Stanford research team Zipeng Fu, Tony Z. Zhao, and Chelsea Finn for their research on Mobile ALOHA, which enabled full open-source implementation. For more details about this project, please check out the link.

Based on Mobile Aloha, AgileX developed Cobot Magic, which can achieve the complete code of Mobile Aloha, with higher configurations and lower costs, and is equipped with larger-load robotic arms and high-computing power industrial computers.

AgileX Cobot Magic is a system based on Mobile ALOHA that can simultaneously remotely control the TRACER mobile base and robotic arms. It is equipped with an indoor differential drive AGV base, a high-performance robotic arm, an industrial-grade computer, and other components. AgileX Cobot Magic assists users in better utilizing open-source hardware and the Mobile ALOHA deep learning framework for robotics. It covers a wide range of tasks, from simple pick-and-place operations to more intricate and complex actions such as pouring, cooking, riding elevators, and organizing items.

Features

Its hardware is based on 4 robotic arms , equipped with 2 wrist cameras and 1 top camera, and a mobile base from AgileX Robotics Tracer differential motion robot.

Standard Configuration

Speed and Performance