5 accepted papers
Inertial Measurement Unit (IMU) plays an important role in inertial aided navigation on robots. However, raw IMU data could be noisy, especially for low-cost IMUs, and thus requires efficient pre-processing or denoising before applying further navigation algorithms. Conventional IMU denoising approa
Modern autonomous vehicles rely heavily on mechanical LiDARs for perception. Current perception methods generally require <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$360^\circ$</tex-math></inline-formula> point
Most autonomous vehicles (AVs) rely on LiDAR and RGB camera sensors for perception. Using these point cloud and image data, perception models based on deep neural nets (DNNs) have achieved state-of-the-art performance in 3D detection. The vulnerability of DNNs to adversarial attacks have been heavil…
Recent studies show that small perturbations in video frames could misguide single object trackers. However, such attacks have been mainly designed for digital-domain videos (i.e., perturbation on full images), which makes them practically infeasible to evaluate the adversarial vulnerability of trac…
Accurate LiDAR-camera online calibration is critical for modern autonomous vehicles and robot platforms. Dominant methods heavily rely on hand-crafted features, which are not scalable in practice. With the increasing popularity of deep learning (DL), a few recent efforts have demonstrated the advant