Nero 7-Axis Robotic Arm

Name: Nero 7-Axis Robotic Arm - AgileX Robotics
Brand: AgileX
SKU: 8ba4db50-31bb-4135-86a9-905f953d50b2
Price: 2400 EUR
Availability: InStock

AgileX | A-000000-07951

€2,400.00 VAT incl. €2,000.00 VAT excl.

The Nero is a 7-axis (7-DoF) robotic arm designed for research work in humanoid robotics and Embodied AI. Its lightweight design and open architecture make laboratory integration, experimentation, and deployment across different setups (tabletop, side mounting, inverted) easier.

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A 7-axis arm built for dexterity, precision, and software integration

7-DoF dexterity, payload and repeatability

With its 7-DoF structure, the Nero aims to provide a wide spatial workspace and wrist-like dexterity close to human motion. It relies on in-house developed motors and a body weighing around 4.8 kg, capable of handling a 3 kg payload. The ±0.1 mm repeatability supports tasks requiring reproducible execution, notably within test protocols and data collection workflows.

R&D control and software integration (CAN/HTTP/TCP, Python, ROS)

Control is designed for R&D use: CAN, HTTP and TCP interfaces, as well as multiple operation modes (for example drag teaching, offline trajectories, API, PC control). Integration with common robotics environments is streamlined via a Python SDK and ROS 1 / ROS 2 compatibility. The arm can also be combined with an AgileX mobile base to build a complete experimentation platform oriented toward an Embodied Platform.

Modular mechanical interfaces for grippers, dexterous hands and tools

On the mechanical side, the modular approach targets compatibility with various end-effectors: grippers, dexterous hands and other tools, so the system can be adapted to experimental protocol needs (physical interaction, manipulation, imitation learning, etc.).

Research use cases: humanoid robotics, learning, and capability validation

Embodied AI: end-to-end validation of perception → decision → action pipelines (control, execution, and evaluation).
Humanoid robotics: experiments on dexterity, 7-axis kinematics, and “human-like” manipulation.
Imitation learning: demonstrations via drag teaching, dataset creation, and policy comparison.
Reinforcement learning: repeatable trajectory execution, robustness testing, and interaction scenarios.
Physical interaction data collection: dataset generation for analysis and training (interaction quality and reproducibility).
ROS integration: application prototyping (ROS 1 / ROS 2) and development of experimental pipelines.
Mobile platform: integration with an AgileX mobile base to test mobile manipulation scenarios.

Technical specifications of the AgileX Nero arm

Degrees of freedom: 7
Reach: 580 mm
Weight: 4.8 kg
Payload: 3 kg
Repeatability: ±0.1 mm
Input voltage: DC 24 V
Noise: < 60 dB
Communication: CAN, HTTP, TCP
Control methods: drag teaching, offline trajectory, API, PC
Software compatibility: Python SDK, ROS 1, ROS 2
External interfaces: Power ×1, CAN ×1, Network ×1
Power consumption: max power < 120 W; average power < 40 W
Operating environment: 0–50°C; 25–85% RH, non-condensing
Mounting: table / side / inverted (upside down)
Base installation dimensions: 70 mm × 70 mm; M5 × 4
Max joint speed: J1 180°/s, J2 180°/s, J3 180°/s, J4 225°/s, J5 225°/s, J6 225°/s, J7 225°/s
Joint range of motion: J1 -157° to 157°, J2 -15° to 190°, J3 -160° to 160°, J4 -60° to 125°, J5 -160° to 160°, J6 -43° to 58°, J7 -90° to 90°