MITO is the first millimeter‑wave dataset featuring diverse everyday objects, collected with a UR5 robotic arm equipped with two mmWave radars and an RGB‑D camera. It includes over 24 million mmWave frames, 550 high‑resolution mmWave images in both line‑of‑sight and non‑line‑of‑sight conditions, along with RGB‑D images, segmentation masks, and raw signals for 76 objects. An open‑source simulator is provided to generate synthetic mmWave images from any 3D triangle mesh, and benchmarks for NLOS segmentation and classification are established to showcase the dataset’s utility.
arXiv:2606. 28396v1 Announce Type: cross Abstract: Millimeter-wave (mmWave) radar perception is limited by data scarcity: models trained on existing radar datasets fail to generalize to new objects, environments, and sensing trajectories.
arXiv:2608. 14179v1 Announce Type: new Abstract: Large language models (LLMs) have shown remarkable reasoning and generative capabilities, motivating their use as universal reasoning engines for perception.
arXiv:2611.08342v1 Announce Type: cross Abstract: Millimeter-wave radar resolves the micrometer displacements of a moving body as micro-Doppler, enabling gait, gesture, activity, pose and vital-sign...
arXiv:2610.34085v1 Announce Type: cross Abstract: Safe indoor operation requires autonomous tracking of objects that are not directly visible to the robot. Optical non-line-of-sight (NLoS) methods de...
arXiv:2609.36844v1 Announce Type: new Abstract: Transparent surfaces are ubiquitous in built environments, yet they remain a persistent failure case for robotic perception. RGB cameras perceive the b...
arXiv:2608.28913v1 Announce Type: cross Abstract: High-resolution 3D radar data is scarce. Commodity mmWave sensors use small antenna arrays that limit angular resolution to several degrees, and exis...
arXiv:2609.34220v2 Announce Type: replace-cross Abstract: Assistive robots increasingly operate in many human-centered environments and perform various human-robot interaction (HRI) tasks, such as ob...
The paper introduces 3D Point Splatting (3DPS), a differentiable point renderer for millimeter-wave radar that directly implements the radar equation with an explicit material model and complex-valued outputs. Unlike prior methods, 3DPS simultaneously provides physical fidelity, complex-valued rendering, and multi-viewpoint tractability, enabling a single optimized scene to generate ADC, complex range profile, and range-azimuth images via FFT pipelines. On six outdoor ColoRadar scenes, 3DPS achieves a mean Pearson correlation of 0.587 on held-out range-azimuth images, outperforming optical-NVS baselines by 1.7x to 5.2x, and trains in about three minutes per scene on an RTX 4090.
Assistive robots increasingly operate in many human-centered environments and perform various human-robot interaction (HRI) tasks, such as object delivery. However, most existing HRI systems rely on R...
The paper introduces 3D Point Splatting (3DPS), a differentiable point renderer for millimeter‑wave radar that directly implements the radar equation with an explicit material model and complex‑valued outputs. Unlike previous methods, 3DPS preserves phase information and supports multiple output formats (ADC, CRP, RA) without retraining. On six outdoor ColoRadar scenes, it achieves a mean Pearson correlation of 0.587 on held‑out RA images, outperforming optical‑NVS baselines by 1.7× to 5.2× and trains in roughly three minutes per scene on a single RTX 4090.
The review surveys 4D millimeter‑wave radar perception algorithms for autonomous driving, covering signal processing, object detection, semantic segmentation, motion estimation, occupancy prediction, and dynamic scene reconstruction. It organizes the field by perception tasks, discusses radar fundamentals, data representations, and quality‑enhancement methods, and compares radar‑only learning, multimodal fusion, and cross‑modal supervision. The paper also summarizes datasets, annotations, evaluation protocols, and outlines common challenges and future research directions.
arXiv:2412.11325v2 Announce Type: replace Abstract: 3D human mesh reconstruction (HMR) from RGB images often degrades under poor illumination, occlusion, and non-line-of-sight conditions. Acoustic se...