Cell-based update algorithm for occupancy grid maps and hybrid map for ADAS on embedded GPUs

Fickenscher, Jörg; Schlumberger, Jens; Hannig, Frank; Teich, Jürgen; Bouzouraa, Mohamed Essayed

doi:10.23919/date.2018.8342050

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…They are also used extensively in the self-driving car industry, since they can deal with a wide variety of environments under diverse conditions of illumination and traffic [24], addressing problems such as road boundary detection [25]. In this domain performance is a critical factor and methods tend to take full advantage of GPU implementations [26].…”

Section: A Applicationsmentioning

confidence: 99%

OHM: GPU Based Occupancy Map Generation

Stepanas¹,

Williams²,

Hernández³

et al. 2022

Preprint

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Occupancy grid maps (OGMs) are fundamental to most systems for autonomous robotic navigation. However, CPU-based implementations struggle to keep up with data rates from modern 3D lidar sensors, and provide little capacity for modern extensions which maintain richer voxel representations. This paper presents OHM, our open source, GPU-based OGM framework. We show how the algorithms can be mapped to GPU resources, resolving difficulties with contention to obtain a successful implementation. The implementation supports many modern OGM algorithms including NDT-OM, NDT-TM, decay-rate and TSDF. A thorough performance evaluation is presented based on tracked and quadruped UGV platforms and UAVs, and data sets from both outdoor and subterranean environments. The results demonstrate excellent performance improvements both offline, and for online processing in embedded platforms. Finally, we describe how OHM was a key enabler for the UGV navigation solution for our entry in the DARPA Subterranean Challenge, which placed second at the Final Event.

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Section: A Applicationsmentioning

confidence: 99%

OHM: GPU Based Occupancy Map Generation

Stepanas¹,

Williams²,

Hernández³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Next, we describe common line marching algorithms used in a diverse set of applications, including: i) ray tracing [127], ii) path planning [128], and iii) generation of occupancy grid maps for autonomous vehicles [129]. These algorithms are chosen as our baseline in this thesis.…”

Section: Line Marching Algorithmsmentioning

confidence: 99%