arXiv 2408.061132024-08-12cs.RO

IIT Bombay Racing Driverless：面向 Formula Student AI 的自动驾驶技术栈

IIT Bombay Racing Driverless: Autonomous Driving Stack for Formula Student AI

Indian Institute of Technology Bombay（印度理工学院孟买分校）

Yash Rampuria, Deep Boliya, Shreyash Gupta, Gopalan Iyengar, Ayush Rohilla, Mohak Vyas, Chaitanya Langde, Mehul Vijay Chanda, Ronak Gautam Matai, Kothapalli Nam… 展开作者

Yash Rampuria, Deep Boliya, Shreyash Gupta, Gopalan Iyengar, Ayush Rohilla, Mohak Vyas, Chaitanya Langde, Mehul Vijay Chanda, Ronak Gautam Matai, Kothapalli Namitha, Ajinkya Pawar, Bhaskar Biswas, Nakul Agarwal, Rajit Khandelwal, Rohan Kumar, Shubham Agarwal, Vishwam Patel, Abhimanyu Singh Rathore, Amna Rahman, Ayush Mishra, Yash Tangri

备注：: 8 pages, 19 figures

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AI总结：

本文介绍 IIT Bombay Racing 面向 Formula Student-AI 赛事的自动驾驶赛车技术栈，融合多传感器、深度学习与控制系统，并通过四轮机器人和仿真验证感知、SLAM、规划与控制算法。

摘要：

本工作介绍了 IIT Bombay Racing 的 Formula Student 风格自动驾驶赛车算法的设计与开发，该算法能够参加在英国举行的 Formula Student-AI 赛车赛事。赛车采用尖端传感器套件，包括计算单元 NVIDIA Jetson Orin AGX、2 台 ZED2i 立体相机、1 个 Velodyne Puck VLP16 LiDAR 以及 SBG Systems Ellipse N GNSS/INS IMU。其特点是利用深度学习算法和控制系统，在无任何人工干预的情况下穿越复杂赛道并执行机动动作。设计过程包含大量仿真和测试，以优化车辆性能并确保安全性。算法已在一个小规模、内部制造的四轮机器人上以及仿真软件中完成测试。文中详细给出了感知、同步定位与地图构建、路径规划和控制等各类算法的测试结果。

英文摘要：

This work presents the design and development of IIT Bombay Racing's Formula Student style autonomous racecar algorithm capable of running at the racing events of Formula Student-AI, held in the UK. The car employs a cutting-edge sensor suite of the compute unit NVIDIA Jetson Orin AGX, 2 ZED2i stereo cameras, 1 Velodyne Puck VLP16 LiDAR and SBG Systems Ellipse N GNSS/INS IMU. It features deep learning algorithms and control systems to navigate complex tracks and execute maneuvers without any human intervention. The design process involved extensive simulations and testing to optimize the vehicle's performance and ensure its safety. The algorithms have been tested on a small scale, in-house manufactured 4-wheeled robot and on simulation software. The results obtained for testing various algorithms in perception, simultaneous localization and mapping, path planning and controls have been detailed.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。