Robot Control
Experimental Device
angel KIT CE10

Embedded Systems
Motor with friction compensation
Smooth Robot Control

The paradigm of robot control is shifting The paradigm of robot control is shifting from position mode control, which reduces tracking error based on specified angle/position trajectories, to force mode control, which precisely generates force/torque to adapt to complex conditions and environments. Wearable robots, in particular, represent a prime example of force mode control systems that require precise force implementation for natural assistance. Additionally, reinforcement learning-based systems also necessitate force mode control, as the dynamic difference (Sim2Real Gap) between simulation and reality must be minimized. Are you interested in learning and using this evolving robot control paradigm in educational processes? Angel Robotics provides control experiment devices for such purposes.

Feature 01

Robot Control Experimental Device with reinforcement learning


To allow direct experience and experimentation with force mode control systems and controllers based on artificial intelligence, we offer the control experiment device (angel KIT CE10).
angel KIT CE10 features a leg-shaped structure with a pair of Angel Robotics' wearable robot actuators (angel KIT AM10) and motor drivers (angel KIT MD10) linked together, with the capability to attach additional weights at the end-effector. It also includes a high-performance AI module, enabling the implementation of artificial neural network algorithms.




Feature 02

What types of control learning and practical applications can be achieved with angel KIT CE10?


  • Robot joint control based on embedded systems
  • Actuator control interacting with sensors
  • Joint trajectory implementation using position control
  • Resistance sensation reduction in joint movements through gravity compensation control
  • Smooth robot control via impedance control

Product Features

  • 01
    Embedded

    Systems

    Robot joint control based on embedded systems

  • 02
    Exceptional Interconnectivity

    Actuator control that interacts with sensors

  • 03
    Joint Trajectory Implementation

    Implementation of joint trajectories
    using position control

  • 04
    Reduction of

    Resistance Sensation

    Reduction of resistance sensation in joint movements through gravity compensation control

  • 05
    Smooth Control

    Smooth robot control via impedance control

Product Configuration

Product Details

Robot Size Robot Size 28 * 65 * 49 cm
Weight 16 kg
Joint Hip Flexion 130˚
Hip Extension 30˚
Knee Flexion 120˚
Knee Extension
System
Specification
Power 48V, 4000mAh with Battery
Application Processor 21 TOPS AI, GPU with 48 Tensor Cores, ARMv8.2 8-core CPU
Micro Controller 32bit ARM M7
Storage eMMC 16GB, SSD 128GB
Wireless 11ac DBDS, BT5.0
Wired CAN-FD
IMU 2EA
Encorder 4EA
Thermal Sensors 2EA
USB Type-C, Type-A : 2EA
Video HDMI 2.0
Audio Stereo
Display LED for BAT. Level
Button Power
SW support Application Processor Ubuntu
Micro Controller Non-RTOS with C
Control Input Support @ Windows PC
Actuator Size and Weight Ø85x55mm, 700g
Max. Torque 15Nm @180 RPM
Max. Power 200W