Hardware components
The open-source humanoid robot product EC-Hunter80-V01 features a unique leg design, without an upper body and arms. Unnecessary external components of the robot's appearance have been removed, retaining only the essential structural elements to achieve maximum lightweight design. This is similar to the approach taken by the foreign company Agility Robotics, where the lower body of their humanoid robot prototype Cassie adopts the classic "ostrich legs," showcasing a minimalist engineering and mechanical design.In terms of hardware specifications, EC-Hunter80-V01 stands at a height of 785.97mm, with a front-back width of 178mm and a left-right width of 330.4mm. The overall structure has 10 degrees of freedom, and the robot weighs approximately 12kg. It is equipped with a 5300mAh lithium battery, along with two power interfaces: 5V10A and 19V12.5A. The openness and compatibility of the control system and electric drive components are commendable.
On the control module, EC-Hunter80-V01 utilizes the NUCWSKI7 control platform and EtherCAT control interface. The EtherCAT interface employs ENCOS's independently developed high-speed EtherCAT to CAN module. A single module with six motors can achieve a maximum communication frame rate of 1kHz, while a module with two motors can achieve a maximum communication frame rate of 2kHz. The use of EtherCAT to CAN modules facilitates the convenient connection between the Linux system and the joint motors. CAN communication boasts high reliability, strong anti-interference capabilities, low cost, and a small interface size. EtherCAT, on the other hand, uses RJ45 ports with a larger physical size but allows for the transmission of a large amount of data at once, making it suitable for connection with systems like Linux. Therefore, using EtherCAT to CAN for the connection between joint modules and the control platform in a legged robot is a good choice.Additionally, it's worth noting that the robot's Inertial Measurement Unit (IMU) also employs a module using ENCOS's EtherCAT bus, operating on the same bus as the motor control. This not only simplifies the overall hardware architecture but also ensures real-time communication.
The EC-Hunter80-V01 main body is extremely lightweight, weighing just over ten kilograms, yet it can carry a payload of up to 15kg. Users have the flexibility to modify and enhance the robot's structure on the hardware level, such as adding dual arms or even quadruple arms, as well as integrating visual systems and other improvements. The lightweight design of EC-Hunter80-V01 is attributed to ENCOS Intelligent Technology's two highly competitive lightweight products, the EC-A8112-P1-18 and EC-A4310-P2-36. The combination of these two in-house developed joint products not only simplifies the design structure of humanoid robots, reducing maintenance complexity and minimizing wiring, but also eliminates the time-consuming process of integrating different products. The overall stability of the software and hardware is noticeably enhanced.In terms of performance, both products achieve a peak torque density of over 100Nm/kg, providing robust power for the motion of bipedal humanoid robots.
Control components
The motion control algorithm for the open-source EC-Hunter80-V01 robot adopts a Model-based control approach, utilizing the MPC (Model Predictive Control) + WBC (Whole-Body Control) algorithm framework. This algorithm integrates modules such as localization perception, gait planning, and ground reaction force calculation to achieve torque-mixed control for legged robots. The control algorithm is provided by Bridgedp Robotics, a startup company formed by members from domestic and international universities, including Southern University of Science and Technology, Beihang University, Huazhong University of Science and Technology, and Tsinghua University. The company is dedicated to developing motion control technology and modular products for humanoid and quadruped robots.Within six months of its establishment, the team demonstrated remarkable research and development capabilities, achieving a breakthrough in stabilizing the walking control of bipedal humanoid robots from scratch within one month. The team plans to continue investing in cutting-edge areas such as robot reinforcement learning, imitation learning, and the development of the humanoid robot motion "cerebellum" module.
