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| Main Authors: | , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.06113 |
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| _version_ | 1866929456108535808 |
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| author | Rampuria, Yash Boliya, Deep Gupta, Shreyash Iyengar, Gopalan Rohilla, Ayush Vyas, Mohak Langde, Chaitanya Chanda, Mehul Vijay Matai, Ronak Gautam Namitha, Kothapalli Pawar, Ajinkya Biswas, Bhaskar Agarwal, Nakul Khandelwal, Rajit Kumar, Rohan Agarwal, Shubham Patel, Vishwam Rathore, Abhimanyu Singh Rahman, Amna Mishra, Ayush Tangri, Yash |
| author_facet | Rampuria, Yash Boliya, Deep Gupta, Shreyash Iyengar, Gopalan Rohilla, Ayush Vyas, Mohak Langde, Chaitanya Chanda, Mehul Vijay Matai, Ronak Gautam Namitha, Kothapalli Pawar, Ajinkya Biswas, Bhaskar Agarwal, Nakul Khandelwal, Rajit Kumar, Rohan Agarwal, Shubham Patel, Vishwam Rathore, Abhimanyu Singh Rahman, Amna Mishra, Ayush Tangri, Yash |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_06113 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | IIT Bombay Racing Driverless: Autonomous Driving Stack for Formula Student AI Rampuria, Yash Boliya, Deep Gupta, Shreyash Iyengar, Gopalan Rohilla, Ayush Vyas, Mohak Langde, Chaitanya Chanda, Mehul Vijay Matai, Ronak Gautam Namitha, Kothapalli Pawar, Ajinkya Biswas, Bhaskar Agarwal, Nakul Khandelwal, Rajit Kumar, Rohan Agarwal, Shubham Patel, Vishwam Rathore, Abhimanyu Singh Rahman, Amna Mishra, Ayush Tangri, Yash Robotics 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. |
| title | IIT Bombay Racing Driverless: Autonomous Driving Stack for Formula Student AI |
| topic | Robotics |
| url | https://arxiv.org/abs/2408.06113 |