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AgileX Cobot Magic
Arm Count
4.0
Payload Capacity
1.5 kg
Teleoperation method (reported)
Leader-follower kinesthetic teleoperation (operator back-drives 2 leader arms; 2 follower arms mirror in real time), with simultaneous mobile-base driving, per the Mobile ALOHA architecture.
Mobile Base
Yes

Overview

Cobot Magic is AgileX Robotics' productized implementation of Stanford's Mobile ALOHA whole-body bimanual manipulation system. An operator physically back-drives the two leader arms and the follower arms mirror the motion in real time (leader-follower teleoperation), while the wheeled base can be driven simultaneously — enabling collection of coordinated whole-body demonstration data. The two follower arms and mobile base form the deployable robot; the two leader arms are the teleoperation input. The system ships with the Mobile ALOHA / ACT (ACT++) imitation-learning codebase adapted by AgileX and a ROS integration layer. It exists in a full mobile version (Tracer base, catalogued here) and a split version (Ranger Mini 3.0 base + docking station + Livox Mid-360 LiDAR).

Highlights

  • Productized Mobile ALOHA: four 6-DoF AgileX PiPER arms in a 2-leader + 2-follower teleoperation rig
  • Simultaneous whole-body teleoperation — arms plus AgileX Tracer mobile base — for demonstration data collection
  • Three Orbbec Dabai RGB-D cameras (2 wrist + 1 top) for imitation-learning perception
  • Ships with the open-source Mobile ALOHA / ACT imitation-learning stack and ROS integration
  • Available as a full mobile version (Tracer base) and a split version (Ranger Mini 3.0 + Livox Mid-360 LiDAR)

Specifications

Configuration

Arm Count
4.0
Teleoperation method (reported)
Leader-follower kinesthetic teleoperation (operator back-drives 2 leader arms; 2 follower arms mirror in real time), with simultaneous mobile-base driving, per the Mobile ALOHA architecture.
Mobile Base
Yes
Leader Arms Included
Yes

Per-Arm Specs

Payload Capacity
1.5 kg
Arm Degrees of Freedom (per arm)
6.0
Maximum Reach
626.75 mm
Repeatability
0.1 mm

Perception

RGB-D Camera Count
3.0

Software & Ecosystem

Onboard Compute
Industrial-grade computer; configurations documented as NVIDIA Jetson Orin Nano Developer Kit (8GB) or an Industrial PC (Intel i7-9700, NVIDIA RTX 4060, 32GB RAM), Ubuntu 20.04 / CUDA 11.3.
ROS/ROS 2 Integration
Yes
Open-Source Assets Included
Mobile ALOHA imitation-learning framework (ACT / ACT++ policy codebase) adapted by AgileX, plus a ROS-based teleoperation and data-collection stack (Stanford Mobile ALOHA lineage).