AGIBOT D1 Edu
About This Robot
AGIBOT D1 Edu (Standard)
Overview
The AGIBOT D1 Edu is a compact and powerful quadruped development platform specifically engineered for the needs of scientific research, higher education, and custom robotics projects. It serves as an open and accessible tool for developers to explore advanced locomotion, integrate custom payloads, and experiment with remote-control systems. Weighing just 15.5 kg, it combines impressive agility with a practical 5 kg payload capacity, making it a versatile base for innovation.
As a developer-focused platform, the D1 Edu is designed for secondary development. While it offers exceptional remotely operated mobility out of the box, functions such as autonomous navigation, following, or inspection require customer-led development using its comprehensive SDK and standardized interfaces. This makes it an ideal choice for teams looking to build and test their own software solutions on a robust hardware foundation.
Key Features
- Dynamic Mobility: Achieves a top speed of 3.5 m/s, can jump up to 35 cm, and continuously climb stairs up to 16 cm high.
- Advanced Gait Control: Utilizes a reinforcement-learning-based gait control system, enabling stable and adaptive movement across varied and challenging terrains.
- Open for Development: Features a full Software Development Kit (SDK) and supports URDF models, allowing for deep customization and control.
- Rich Connectivity: Equipped with standardized Ethernet, USB, power, SBUS, and UART interfaces for seamless integration of sensors, communication modules, and other payloads.
- Simulation Ready: Fully compatible with industry-standard simulation environments, including Isaac Sim and MuJoCo, for rapid algorithm testing and virtual prototyping.
- Efficient Power and Payload: Offers a 1-2 hour runtime and carries an effective payload of 5 kg, providing a strong balance of endurance and capability.
Technical Specifications
| Specification | Value |
|---|---|
| Make | AGIBOT |
| Model | D1 Edu |
| Variant | Standard |
| Weight | 15.5 kg |
| Effective Payload | 5 kg |
| Maximum Speed | 3.5 m/s |
| Approximate Runtime | 1-2 hours |
| Continuous Stair Climbing | 16 cm |
| Jumping Height | 35 cm |
| Gait Control | Reinforcement-learning-based |
| Development Interfaces | SDK, Ethernet, USB, Power, SBUS, UART |
| Simulation Support | URDF Models, Isaac Sim, MuJoCo |
Applications
The AGIBOT D1 Edu is an ideal platform for a wide range of applications, including:
- Robotics Research: Investigating legged locomotion, reinforcement learning, machine vision, and human-robot interaction.
- University Education: Providing a hands-on platform for students in computer science, mechatronics, and engineering to learn and apply advanced robotics concepts.
- Custom Sensor Integration: Serving as a mobile base for testing and deploying custom sensor packages like LiDAR, thermal cameras, or environmental sensors.
- Algorithm Prototyping: Developing and validating autonomous navigation, mapping (SLAM), and object recognition algorithms in real-world scenarios.
Benefits
- Accelerate Research: Provides a reliable and well-supported hardware platform, allowing researchers to focus on software and algorithm development rather than hardware engineering.
- Empower Customization: The open SDK and standard interfaces remove barriers to integration, giving developers the freedom to build highly specialized solutions.
- Bridge Simulation and Reality: Seamless workflows between simulators like Isaac Sim and the physical robot enable faster, safer, and more efficient development cycles.
- Accessible Advanced Robotics: Offers a cost-effective entry point into advanced quadruped robotics for educational institutions and R&D labs without the constraints of a closed, proprietary system.
Key Capabilities
- Reinforcement-learning-based gait control adapts locomotion to varied terrain and supports self-balancing, anti-fall and anti-interference behaviours.
- Agile mobility includes a 3.5 m/s maximum speed, 16 cm continuous stair-climb height, 35 cm vertical jump and a published 30-degree climbing slope on the official store page.
- The 5 kg effective payload supports lightweight research sensors, communications modules and prototype application payloads.
- The Edu version includes an SDK and functional expansion ports: Ethernet x1, USB x2, power x2, SBUS x1 and UART x1.
- Compatible modules include positioning, LiDAR, depth cameras, RTK, 4G/5G and image-transmission hardware.
- URDF models support simulation and testing in Isaac Sim and MuJoCo before deployment to the physical robot.
- A handheld joystick remote and real-time image transmission support teleoperation and live-view experiments.
- A 4.6 Ah, 43.2 V battery provides approximately 1-2 hours of operation and charges from 10% to 90% in about one hour.
Applications
- University and research-lab work on quadruped locomotion, reinforcement learning, motion control and whole-body stability.
- Teaching and student projects covering robotics programming, sensor integration, simulation and real-world deployment.
- Development of autonomous following, navigation and custom mission workflows using the SDK and added perception modules.
- Prototype remote-inspection and telepresence applications using the handheld controller, live image transmission and optional communications modules.
- Testing LiDAR, depth-camera, RTK and positioning payloads for mapping, localisation and field-robotics research.
- Entertainment performances and demonstration programmes using the robot's standard and special actions, including jumps, biped standing, waving and backflips.
Why Choose It
- A commercially orderable education and development quadruped with a published official-store price, reducing procurement uncertainty for labs and teaching programmes.
- The Edu variant adds SDK access and hardware expansion ports that are absent from the lower-cost D1 Pro.
- Compact 15.5 kg weight and dynamic mobility make it easier to transport, demonstrate and test than larger industrial quadrupeds.
- The combination of standardized interfaces, optional sensor modules and URDF simulation support provides a practical path from simulation to hardware.
- Published performance figures cover payload, speed, runtime, stairs, jumping, dimensions, battery and charging, supporting transparent model comparison.
- Buyers should plan for developer-led integration: autonomous following and mission functions are not standard, and AGIBOT states that technical issues are primarily self-supported beyond the hardware warranty.
Key Features
SDK support, URDF models and Isaac Sim/MuJoCo workflows enable secondary development and simulation-led testing.
Ethernet, USB, power, SBUS and UART ports support integration of sensors, communications and custom modules.
Reinforcement-learning gait control supports 3.5 m/s running, 16 cm stair climbing, 35 cm jumping and dynamic special actions.
A 15.5 kg body carries a 5 kg effective payload while remaining practical for labs, classrooms and demonstrations.
The supplied handheld controller and real-time image transmission support teleoperation and rapid field testing.
Technical Details
Not standard; Edu SDK supports development of autonomous following, navigation and custom missions
Standard charger and charging base; about 1 hour from 10% to 90%; battery-swap capability not published
635 x 360 x 420 standing; 675 x 435 x 145 lyingmm
0-40 deg C operating temperature; IP rating not published
5kg
1-2hours
30degrees
3.5m/s
RL-based gait and terrain adaptation; autonomous following/navigation require secondary development and added sensors
SDK; Ethernet x1; USB x2; power x2; SBUS x1; UART x1; supports positioning, LiDAR, depth camera, RTK, 4G/5G and image-transmission modules
Integrated wide-FOV camera (DFOV 122 deg, HFOV 111 deg, VFOV 70 deg) and IMU; optional LiDAR, depth camera, RTK and positioning modules
Joystick handheld remote and real-time image transmission; Ethernet, USB, SBUS and UART; optional 4G/5G and image-transmission modules
15.5kg
Self-balancing, anti-fall and anti-interference behaviours; autonomous obstacle avoidance is not listed as standard and requires development
RL-based terrain adaptation; 16 cm continuous stair-climb height; 35 cm vertical jump; self-balancing and anti-fallmm / text
Manufacturer
AGIBOT
Manufacturer
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