GRCA uses emitter-centric geometric culling of rays per triangle to accelerate LiDAR simulation in arbitrarily dynamic scenes, reporting up to 14.55x speedup over Embree and 7.97x over OptiX.
LGSVL simulator: A high fidelity simulator for autonomous driving,
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CoCoMagic applies constrained cooperative co-evolution to metamorphic and differential testing to find up to 287% more distinct behavioral divergences in an end-to-end ADS than baseline search methods.
Collaborative self-calibration via grid-based Bayesian uncertainty propagation achieves 0.28 m LOS and 1.11 m overall ranging error with sub-meter positioning in real UWB tests with 12 static nodes.
citing papers explorer
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Geometrically Approximated Modeling for Emitter-Centric Ray-Triangle Filtering in Arbitrarily Dynamic LiDAR Simulation
GRCA uses emitter-centric geometric culling of rays per triangle to accelerate LiDAR simulation in arbitrarily dynamic scenes, reporting up to 14.55x speedup over Embree and 7.97x over OptiX.
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Constrained Co-evolutionary Metamorphic Differential Testing for Autonomous Systems with an Interpretability Approach
CoCoMagic applies constrained cooperative co-evolution to metamorphic and differential testing to find up to 287% more distinct behavioral divergences in an end-to-end ADS than baseline search methods.
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Evaluation of Grid-based Uncertainty Propagation for Collaborative Self-Calibration in Indoor Positioning Systems
Collaborative self-calibration via grid-based Bayesian uncertainty propagation achieves 0.28 m LOS and 1.11 m overall ranging error with sub-meter positioning in real UWB tests with 12 static nodes.