用Python打造iCub机器人仿真教学框架，零代码门槛上手
Learning with pyCub: A Simulation and Exercise Framework for Humanoid Robotics
- 基于物理引擎的iCub机器人全关节仿真，支持双摄像头与4000个触觉传感器
- 全程用Python控制，无需C++或YARP，适合编程初学者
- 配套分层练习题，可适配不同难度的人形机器人课程
我们提出pyCub，一个面向人形机器人iCub的开源物理仿真系统，配备教学练习以帮助学生掌握人形机器人基础。相比现有iCub模拟器（iCub SIM、iCub Gazebo），pyCub无需C++代码和YARP中间件，完全基于Python实现。完整机器人模型包含所有关节，配备双眼摄像头及拥有4000个感受器的敏感皮肤。练习内容涵盖速度、关节与笛卡尔空间控制，以及凝视、抓取和反应式控制等复杂任务。整个框架采用Python编写与控制，即使无编程经验者也可使用。练习支持多级难度调整。该框架已在两轮人形机器人课程中验证。仿真、练习、文档、Docker镜像及示例视频均公开于https://rustlluk.github.io/pyCub。
原文摘要 · Abstract (English)
We present pyCub, an open-source physics-based simulation of the humanoid robot iCub, along with exercises to teach students the basics of humanoid robotics. Compared to existing iCub simulators (iCub SIM, iCub Gazebo), which require C++ code and YARP as middleware, pyCub works without YARP and with Python code. The complete robot with all articulations has been simulated, with two cameras in the eyes and the unique sensitive skin of the iCub comprising 4000 receptors on its body surface. The exercises range from basic control of the robot in velocity, joint, and Cartesian space to more complex tasks like gazing, grasping, or reactive control. The whole framework is written and controlled with Python, thus allowing to be used even by people with small or almost no programming practice. The exercises can be scaled to different difficulty levels. We tested the framework in two runs of a course on humanoid robotics. The simulation, exercises, documentation, Docker images, and example videos are publicly available at https://rustlluk.github.io/pyCub.
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