VisionSIM: Beyond Idealized Sensors - A Multi-Modal Simulator for Robot Perception
Overview
This paper introduces VisionSIM, a unified simulation platform designed to improve the realism of robotic perception by modeling the raw physical measurement processes for various conventional and emerging sensor modalities. Unlike existing simulators that idealize sensors, VisionSIM exposes fine-grained control over physical parameters to reproduce critical failure modes specific to each modality, such as pileup and glare for LiDAR, phase wrapping and saturation for iToF, refractory drops for event cameras, and history-dependent emission for thermal cameras. The platform enables principled cross-modality comparison on identical scenes and trajectories. Additionally, the authors release the platform along with a large indoor dataset featuring synchronized raw measurements and rich ground-truth annotations.
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Environment: simulation
“arXiv:2611.08368v1 Announce Type: new Abstract: Robotic perception increasingly relies on heterogeneous sensor suites combining cameras with emerging modalities (event, SPAD, iToF/dToF, and thermal). Yet existing simulators idealize these sensors, hiding critical modality-specific failure modes that limit real-world deployment. We present VisionSIM, a unified, physically grounded simulation platform that elevates sen”
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Artifact availability · dataset: reported pending
“n for thermal cameras. This enables principled cross-modality comparison on identical scenes and trajectories. We release the platform and a large indoor dataset with synchronized raw measurements and rich ground-truth annotations.”
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Dataset · modalities: raw physical measurement process for diverse conventional and emerging modalities
“sor realism to a first-class concern by modeling the raw physical measurement process for diverse conventional and emerging modalities. We expose fine-grained control over physical sensor parameters, reproducing failure modes overlooked by general-purpose simulators: pileup and glare for LiDAR; phase wrapping, saturation, and motion artifacts for iToF; refractory drops for event cameras; and history-dependent emissio”
Exact source · revision 1Source owner not reported
Dataset · embodiments: indoor dataset with synchronized raw measurements and rich ground-truth annotations
“n for thermal cameras. This enables principled cross-modality comparison on identical scenes and trajectories. We release the platform and a large indoor dataset with synchronized raw measurements and rich ground-truth annotations.”
Exact source · revision 1Source owner not reported
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- arXiv Robotics — research abstractsSignalVisionSIM: Beyond Idealized Sensors - A Multi-Modal Simulator for Robot Perception
This paper introduces VisionSIM, a unified simulation platform designed to improve the realism of robotic perception by modeling the raw physical measurement processes for various conventional and emerging sensor modalities. Unlike existing simulators that idealize sensors, VisionSIM exposes fine-grained control over physical parameters to reproduce critical failure modes specific to each modality, such as pileup and glare for LiDAR, phase wrapping and saturation for iToF, refractory drops for event cameras, and history-dependent emission for thermal cameras. The platform enables principled cross-modality comparison on identical scenes and trajectories. Additionally, the authors release the platform along with a large indoor dataset featuring synchronized raw measurements and rich ground-truth annotations.
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