荣耀运动规划与控制高级工程师
校招全职研发类地点:北京 | 上海 | 深圳状态:招聘
任职要求
1、电子信息、自动化、机械电子、计算机等相关专业; 2、掌握机器人学基础理论(正逆运动学、动力学建模); 3、熟练使用C++/Python,具备ROS、强化学习、具身模型等开发经验; 4、熟悉常用控制算法(PID、LQR、阻抗控制等); 5、有机器人竞赛(如RoboMaster、RoboCup)开发经验、发表过机器人运动规划相关会议论文(ICRA/IROS等)、熟悉实时操作系统(RTOS)或车载计算平台部署优先; 6、有生物力学、运动科学、3D人体建模或自动驾驶行人动作预测相关开发经验者优先; 7、有GNN/GCN网络设计和调优经验者优先。
工作职责
1、算法开发与优化:负责机器人运动规划控制算法(如强化学习、WBC、MPC等)的实现与改进,设计多关节系统的运动控制策略,实现高精度轨迹跟踪,开发动态障碍物避障算法,提升系统实时响应能力; 2、仿真与测试:基于ISAAC GYM/ROS/Gazebo搭建机器人运动规划仿真环境,设计典型场景测试用例,输出算法性能分析报告,包括成功率、实时性和鲁棒性指标; 3、系统集成与调试:参与机器人实际平台的算法部署,配合硬件团队进行执行器动态补偿与参数整定; 4、对人体关节、骨骼进行建模,显式或隐式定义关节约束,对给定的末端位置预测各个关节的位置和速度。
包括英文材料
C+++
https://www.learncpp.com/
LearnCpp.com is a free website devoted to teaching you how to program in modern C++.
https://www.youtube.com/watch?v=ZzaPdXTrSb8
Python+
https://liaoxuefeng.com/books/python/introduction/index.html
中文,免费,零起点,完整示例,基于最新的Python 3版本。
https://www.learnpython.org/
a free interactive Python tutorial for people who want to learn Python, fast.
https://www.youtube.com/watch?v=K5KVEU3aaeQ
Master Python from scratch 🚀 No fluff—just clear, practical coding skills to kickstart your journey!
https://www.youtube.com/watch?v=rfscVS0vtbw
This course will give you a full introduction into all of the core concepts in python.
ROS+
https://www.youtube.com/watch?v=92Zz5nnd41c&list=PLk51HrKSBQ8-jTgD0qgRp1vmQeVSJ5SQC
https://www.youtube.com/watch?v=HJAE5Pk8Nyw
Ready to learn ROS2 and take your robotics skills to the next level?
https://www.youtube.com/watch?v=MWKnMPX0Yjg&list=PLU9tksFlQRircAdEplrH9NMm4WtSA8yzi
Do you want to know more about ROS the Robot Operating System?
强化学习+
https://cloud.google.com/discover/what-is-reinforcement-learning?hl=en
Reinforcement learning (RL) is a type of machine learning where an "agent" learns optimal behavior through interaction with its environment.
https://huggingface.co/learn/deep-rl-course/unit0/introduction
This course will teach you about Deep Reinforcement Learning from beginner to expert. It’s completely free and open-source!
https://www.kaggle.com/learn/intro-to-game-ai-and-reinforcement-learning
Build your own video game bots, using classic and cutting-edge algorithms.
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
RTOS+
[英文] RTOS Fundamentals
https://www.freertos.org/Documentation/01-FreeRTOS-quick-start/01-Beginners-guide/01-RTOS-fundamentals
A Real-Time Operating System (RTOS) is a type of computer operating system designed to be small and deterministic.
自动驾驶+
https://www.youtube.com/watch?v=_q4WUxgwDeg&list=PL05umP7R6ij321zzKXK6XCQXAaaYjQbzr
Lecture: Self-Driving Cars (Prof. Andreas Geiger, University of Tübingen)
https://www.youtube.com/watch?v=NkI9ia2cLhc&list=PLB0Tybl0UNfYoJE7ZwsBQoDIG4YN9ptyY
You will learn to make a self-driving car simulation by implementing every component one by one. I will teach you how to implement the car driving mechanics, how to define the environment, how to simulate some sensors, how to detect collisions and how to make the car control itself using a neural network.
GNN+
https://distill.pub/2021/gnn-intro/
Neural networks have been adapted to leverage the structure and properties of graphs.
https://gnn.seas.upenn.edu/
Graph Neural Networks (GNNs) are information processing architectures for signals supported on graphs.
https://www.ibm.com/think/topics/graph-neural-network
Graph neural networks (GNNs) are a deep neural network architecture that is popular both in practical applications and cutting-edge machine learning research.
相关职位
社招自动驾驶
1.负责结构化/非结构化全场景自动驾驶解决方案中决策规划算法开发与验证; 2.负责决策规划算法架构设计与实现,工程软件规范化与质量效率提升; 3.负责量产自动驾驶规划控制算法的开发和部署,确保整车安全性,并对实车测试问题进行分析定位和持续迭代优化; 4.高效自动化算法开发迭代工具设计与实现,高准确性算法评测系统搭建。
校招研发类
1.三维导航系统开发:基于激光/视觉SLAM实现动态场景重建,开发多目标路径规划算法 ,设计运动学控制接口,适配UR/Unitree等机器人平台; 2.多模态模型工程化:优化视觉语言模型在导航任务中的推理效率,实现多传感器标定工具链,构建仿真-真机数据闭环系统; 3.导航智能体开发:面向导航的任务规划与决策等模块开发,设计知识图谱增强的检索系统 ,探索多智能体协作策略; 4.技术文档编写:编写软件设计文档、调试报告及相关技术资料。
更新于 2025-05-15