杨俊杰 (Yang Junjie)

杨俊杰于中山大学(中国广州)机器人与智能计算研究组在黄凯教授的指导下获得了他的学士学位(软件工程)和硕士学位(软件工程)。目前,他(将)以中国国家公派留学生身份前往德国慕尼黑工业大学在 Chris P. Lohmann 教授和 Ali Nasseeri 博士的共同指导下攻读博士学位,研究方向为医疗机器智能。他的研究兴趣包括自动驾驶技术、嵌入式系统技术与医疗机器智能。他曾获得2016-2017年度中山大学优秀团员称号、2017年中国嵌入式系统年会最佳论文奖、2017年中国无人船公开赛优秀团队奖、2018年中山大学优秀毕业论文奖。

Yang Junjie obtained his Bachelor’s Degree of Software Engineering and Master’s Degree of Software Engineering under the supervision of Prof. Huang Kai in Robotics and Intelligent Computing Lab of Sun Yat-Sen University, China. Currently he is pursuing his Ph.D. on surgery arms with Prof. Chris P. Lohmann and Dr. Ali Nasseri in Technical University of Munich, Germany. His research interests include embedded system techniques and medical robotic intelligence.

参与论文发表

参与工程项目

眼科手术机械臂 Eye-Surgery Robot

目前正在眼科手术机器人的机械结构与控制算法研究,主要研究主题为机器人状态估计算法、路径规划算法和智能医疗图像处理。

Currently he is doing researches on mechanical structures and controlling algorithms about status estimation, path planning, and intelligent medical image processing.

自动驾驶软件分析 Analysis of Autonomous Driving Software

针对自动驾驶控制器软件,通过比较不同触发方式对应代码实现的周期性执行性能和最终输出性能来探索适合自动驾驶场景的代码实现方法和资源调度方法。相关研究内容已形成论文与专利数篇。

Targeting at autonomous driving controllers, the difference of time-triggered and event-triggered software approaches has been analyzed by outputing the periodical execution results and the final metric to find a suitable controller implementation and its resource scheduling for autonomous driving in various scenarios. Several papers and patterns have been proposed.

自动驾驶硬件调试 Deployment of Autonomous Driving Vehicle

使用GPS、IMU、激光雷达等高精度传感器对自动驾驶车辆进行定位、感知,并使用低功耗嵌入式硬件系统完成障碍物识别、路径规划、车辆姿态规划与控制指令输出。相关研究内容已形成论文与专利数篇。

High-accurate sensors, such as GPS, IMU, and LiDAR, are used in autonomous driving vehicles to finish localization and perception. Low-power embedded hardware is equipped to execute obstacle detection, path planning, pose planning, and command output. Several papers and patterns have been proposed.