Demo Abstract: C-Shenron: A Realistic Radar Simulation Framework for CARLA

The advancement of self-driving technology is driven by the need for robust and efficient perception systems along with frameworks for End-to-End testing, enabled by the CARLA simulator. We introduce C-Shenron, a novel integration of a realistic radar sensor model within CARLA, enabling researchers to develop and test navigation algorithms using radar data. It is the first realistic radar simulator which utilizes LiDAR and camera sensors to generate high-fidelity radar ADC measurements from physics based modeling of the environment. Utilizing this radar sensor and showcasing its capabilities in simulation, we demonstrate improved performance in end-to-end driving scenarios. Our setup aims to rekindle the interest in radar-based self-driving research and promote the development of algorithms that leverages its strengths.

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Publication Details

Published
2025-05-04
DOI
https://doi.org/10.1145/3715014.3724379
Citations
1
Primary Topic
Computer Graphics and Visualization Techniques
Type
article
Field-Weighted Citation Impact
3.54
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Demo Abstract: C-Shenron: A Realistic Radar Simulation Framework for CARLA

Kshitiz Bansal, Dinesh Bharadia, J. Li, Pushkal Mishra et al.
1 citations
Computer Graphics and Visualization Techniques
3.54
article

Demo Abstract: C-Shenron: A Realistic Radar Simulation Framework for CARLA

Kshitiz Bansal, Dinesh Bharadia, J. Li, Pushkal Mishra, Satyam Srivastava
article en
1 citations

Abstract

The advancement of self-driving technology is driven by the need for robust and efficient perception systems along with frameworks for End-to-End testing, enabled by the CARLA simulator. We introduce C-Shenron, a novel integration of a realistic radar sensor model within CARLA, enabling researchers to develop and test navigation algorithms using radar data. It is the first realistic radar simulator which utilizes LiDAR and camera sensors to generate high-fidelity radar ADC measurements from physics based modeling of the environment. Utilizing this radar sensor and showcasing its capabilities in simulation, we demonstrate improved performance in end-to-end driving scenarios. Our setup aims to rekindle the interest in radar-based self-driving research and promote the development of algorithms that leverages its strengths.

University of California, Riverside (US), University of California San Diego (US), Birla Institute of Technology and Science, Pilani (IN)
Openalex Percentile: Top 10%
Computer Graphics and Visualization Techniques
3.54
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