130 citations · 525 across the 45 of their papers we have counts for
9 papers · 1 filter
Uncertainty Estimation for 3D Dense Prediction via Cross-Point Embeddings
Kaiwen Cai, Chris Xiaoxuan Lu, Xiaowei Huang
Dense prediction tasks are common for 3D point clouds, but the uncertainties inherent in massive points and their embeddings have long been ignored. In this work, we present CUE, a…
OdomBeyondVision: An Indoor Multi-modal Multi-platform Odometry Dataset Beyond the Visible Spectrum
Peize Li, Kaiwen Cai, Muhamad Risqi U. Saputra +4
This paper presents a multimodal indoor odometry dataset, OdomBeyondVision, featuring multiple sensors across the different spectrum and collected with different mobile platforms.…
Deep Odometry Systems on Edge with EKF-LoRa Backend for Real-Time Positioning in Adverse Environment
Zhuangzhuang Dai, Muhamad Risqi U. Saputra, Chris Xiaoxuan Lu +2
Ubiquitous positioning for pedestrian in adverse environment has served a long standing challenge. Despite dramatic progress made by Deep Learning, multi-sensor deep odometry syste…
DC-Loc: Accurate Automotive Radar Based Metric Localization with Explicit Doppler Compensation
Pengen Gao, Shengkai Zhang, Wei Wang +1
Automotive mmWave radar has been widely used in the automotive industry due to its small size, low cost, and complementary advantages to optical sensors (e.g., cameras, LiDAR, etc.…
AutoPlace: Robust Place Recognition with Single-chip Automotive Radar
Kaiwen Cai, Bing Wang, Chris Xiaoxuan Lu
This paper presents a novel place recognition approach to autonomous vehicles by using low-cost, single-chip automotive radar. Aimed at improving recognition robustness and fully e…
milliEgo: Single-chip mmWave Radar Aided Egomotion Estimation via Deep Sensor Fusion
Chris Xiaoxuan Lu, Muhamad Risqi U. Saputra, Peijun Zhao +6
Robust and accurate trajectory estimation of mobile agents such as people and robots is a key requirement for providing spatial awareness for emerging capabilities such as augmente…
Deep Learning based Pedestrian Inertial Navigation: Methods, Dataset and On-Device Inference
Changhao Chen, Peijun Zhao, Chris Xiaoxuan Lu +3
Modern inertial measurements units (IMUs) are small, cheap, energy efficient, and widely employed in smart devices and mobile robots. Exploiting inertial data for accurate and reli…
OxIOD: The Dataset for Deep Inertial Odometry
Changhao Chen, Peijun Zhao, Chris Xiaoxuan Lu +3
Advances in micro-electro-mechanical (MEMS) techniques enable inertial measurements units (IMUs) to be small, cheap, energy efficient, and widely used in smartphones, robots, and d…
IONet: Learning to Cure the Curse of Drift in Inertial Odometry
Changhao Chen, Xiaoxuan Lu, Andrew Markham +1
Inertial sensors play a pivotal role in indoor localization, which in turn lays the foundation for pervasive personal applications. However, low-cost inertial sensors, as commonly…