DTR: Delaunay Triangulation-based Racing for Scaled Autonomous Racing
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2025
Publication Type
Conference Paper
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yes
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Abstract
Reactive controllers for autonomous racing avoid the computational overhead of full See-Think-Act autonomy stacks by directly mapping sensor input to control actions, eliminating the need for localization and planning. A widely used reactive strategy is Follow-The-Gap (FTG), which identifies gaps in Light Detection and Ranging (LiDAR) range measurements and steers toward a chosen one. While effective on fully bounded circuits, FTG fails in scenarios with incomplete boundaries and is prone to driving into dead-ends, known as FTG-traps. This work presents Delaunay Triangulation-based Racing (DTR), a reactive controller that combines Delaunay triangulation, from raw LiDAR readings, with track boundary segmentation to extract a centerline while systematically avoiding FTG-traps. Compared to FTG, the proposed method achieves lap times that are 70% faster and approaches the performance of map-dependent methods. With a latency of 8.95 ms and Central Processing Unit (CPU) usage of only 38.85% on the robot’s OnBoard Computer (OBC), DTR is real-time capable and has been successfully deployed and evaluated in field experiments.
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published
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Book title
2025 10th International Workshop on Advances in Sensors and Interfaces (IWASI)
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Pages / Article No.
11121997
Publisher
IEEE
Event
10th International Workshop on Advances in Sensors and Interfaces (IWASI 2025)
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Subject
Autonomous driving; Reactive control; Collision avoidance
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01225 - D-ITET Zentr. f. projektbasiertes Lernen / D-ITET Center for Project-Based Learning
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Is new version of: https://doi.org/10.48550/arXiv.2505.24320