Lambda-Field: A Continuous Counterpart of the Bayesian Occupancy Grid for Risk Assessment

Laconte, Johann; Debain, Christophe; Chapuis, Roland; Pomerleau, François; Aufrère, Romuald

doi:10.1109/iros40897.2019.8968100

Cited by 11 publications

(12 citation statements)

References 29 publications

(51 reference statements)

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“…Moreover, the authors in [ 50 ] asserted that all the previously mentioned frameworks were not suitable for assessing meaningful risks, i.e., risks that keep their physical unit. Thus, they proposed a novel framework called Lambda-field, which is based on the Poisson Point Process theory.…”

Section: Traversability Risk Characterizationmentioning

confidence: 99%

A Review on Traversability Risk Assessments for Autonomous Ground Vehicles: Methods and Metrics

Benrabah,

Orou Mousse,

Randriamiarintsoa

et al. 2024

Sensors

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Evaluating the risk associated with operations is an essential element of safe planning and an essential prerequisite in mobile robotics. This issue is very broad, with numerous definitions emerging in the recent literature adapting different application scenarios and leading to different algorithmic approaches. In this review, we will investigate how the state-of-the-art approaches define the traversability risk, particularly for mobile robots, whereby we classify existing risk-aware navigation algorithms according to their characterization of risk. Subsequently, we will overview the formulations of risk assessment along a path using traversability grid maps since it is essential for a mobile robot to evaluate its path to predict potential hazards. Finally, we will discuss the consistency of commonly used risk metrics in robotics. The aim of the review is to offer a comprehensive overview to newcomers in the field, to provide a structured reference for practitioners, and to also inspire future developments.

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Section: Traversability Risk Characterizationmentioning

confidence: 99%

A Review on Traversability Risk Assessments for Autonomous Ground Vehicles: Methods and Metrics

Benrabah,

Orou Mousse,

Randriamiarintsoa

et al. 2024

Sensors

Self Cite

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“…This approach was first proposed by [ 10 ] for robotic applications. The procedure was extended into automotive applications by [ 15 , 16 ] for collision risk estimation and by [ 14 ] for grid-based object tracking. Nonetheless, previous evaluation methods are applicable only for specific test drive scenarios.…”

Section: Definition Of Key Performance Indicators (Kpi)mentioning

confidence: 99%

“…In the literature, there are metrics for object tracking [ 14 ] and for collision risk estimation [ 15 , 16 ]. In the object extraction steps of these methods, the occupancy grid must be carefully analysed and compared with accurate scene descriptions.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of the Highway Radar Occupancy Grid

Porębski

Kogut²

2021

Sensors

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The quality of environmental perception is crucial for automated vehicle capabilities. In order to ensure the required accuracy, the occupancy grid mapping algorithm is often utilised to fuse data from multiple sensors. This paper focuses on the radar-based occupancy grid for highway applications and describes how to measure effectively the quality of the occupancy map. The evaluation was performed using the novel grid pole-like object analysis method. The proposed assessment is versatile and can be applied without detailed ground truth information. The evaluation was tested with a simulation and real vehicle experiments on the highway.

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“…Collision probabilities are used for motion planning under robot position uncertainty [9,3]. Like Euclidean distance and gradient field methods, existing methods that estimate collision probability from a surface point cloud utilize probabilistic occupancy queries from a discrete [20,27] or continuous surface representation [13]. These maps require storing free space cells [11,21,1] or raw point clouds [45], leading arXiv:2402.00186v2 [cs.RO] 17 Apr 2024 to high memory usage.…”

Section: Introductionmentioning

confidence: 99%

Incremental Multimodal Surface Mapping via Self-Organizing Gaussian Mixture Models

Goel,

Tabib

2023

IEEE Robot. Autom. Lett.

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This paper describes continuous-space methodologies to estimate the collision probability, Euclidean distance and gradient between an ellipsoidal robot model and an environment surface modeled as a set of Gaussian distributions. Continuousspace collision probability estimation is critical for uncertaintyaware motion planning. Most collision detection and avoidance approaches assume the robot is modeled as a sphere, but ellipsoidal representations provide tighter approximations and enable navigation in cluttered and narrow spaces. State-of-theart methods derive the Euclidean distance and gradient by processing raw point clouds, which is computationally expensive for large workspaces. Recent advances in Gaussian surface modeling (e.g. mixture models, splatting) enable compressed and high-fidelity surface representations. Few methods exist to estimate continuous-space occupancy from such models. They require Gaussians to model free space and are unable to estimate the collision probability, Euclidean distance and gradient for an ellipsoidal robot. The proposed methods bridge this gap by extending prior work in ellipsoid-to-ellipsoid Euclidean distance and collision probability estimation to Gaussian surface models. A geometric blending approach is also proposed to improve collision probability estimation. The approaches are evaluated with numerical 2D and 3D experiments using real-world point cloud data. Methods for efficient calculation of these quantities are demonstrated to execute within a few microseconds per ellipsoid pair using a single-thread on low-power CPUs of modern embedded computers.

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Lambda-Field: A Continuous Counterpart of the Bayesian Occupancy Grid for Risk Assessment

Cited by 11 publications

References 29 publications

A Review on Traversability Risk Assessments for Autonomous Ground Vehicles: Methods and Metrics

A Review on Traversability Risk Assessments for Autonomous Ground Vehicles: Methods and Metrics

Performance Evaluation of the Highway Radar Occupancy Grid

Incremental Multimodal Surface Mapping via Self-Organizing Gaussian Mixture Models

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