13 accepted papers
DUSt3R-based end-to-end scene reconstruction has recently shown promising results in dense visual SLAM. However, most existing methods only use image pairs to estimate pointmaps, overlooking spatial memory and global consistency. To this end, we introduce GRS-SLAM3R, an end-to-end SLAM framework for…
4D imaging radar is a type of low-cost millimeter-wave radar(costing merely 10-20% of lidar systems) capable of providing range, azimuth, elevation, and Doppler velocity information. Accurate extrinsic calibration between millimeter-wave radar and camera systems is critical for robust multimodal per
Neural implicit scene representations have recently shown promising results in dense visual SLAM. However, existing implicit SLAM algorithms are constrained to single-agent scenarios, and fall difficulty in large indoor scenes and long sequences. Existing multi-agent SLAM frameworks cannot meet the…
Recent research has begun exploring novel view synthesis (NVS) for LiDAR point clouds, aiming to generate realistic LiDAR scans from unseen viewpoints. However, most existing approaches do not reconstruct semantic labels, which are crucial for many downstream applications such as autonomous driving
Nonlinear dynamics bring difficulties to controller design for control-affine systems such as tractor-trailer vehicles, especially when the parameters in the dynamics are unknown. To address this constraint, we propose a derivative-based lifting function construction method, show that the correspond…
Neural implicit scene representations have recently shown encouraging results in dense visual SLAM. However existing methods produce low-quality scene reconstruction and low-accuracy localization performance when scaling up to large indoor scenes and long sequences. These limitations are mainly due…
Prior structural reference like floor plan is readily accessible in indoor scene, which exhibits the potential of improving localization quality without the requirements of a previously-built high-precision map. This paper introduces a novel optimal transport-based framework for prior structural ref…
"Although LiDAR semantic segmentation advances rapidly, state-of-the-art methods often incorporate specifically designed inductive bias derived from benchmarks originating from mechanical spinning LiDAR. This can limit model generalizability to other kinds of LiDAR technologies and make hyperparamet…
The main content of the research in this paper is the estimation of depth and pose based on monocular vision and Inertial Measurement Unit (IMU). The usual depth estimation network and pose estimation network require depth ground truth or pose ground truth as a supervised signal for training, while…
This study proposes a hybrid vision/force control scheme for interaction with the inner surface of the bottle-like object. Based on the geometry of the object, a new generalized constraint called the bottleneck (BN) constraint is proposed, which ensures the tool passes through a fixed 3-D region and…
Accurate, robust and real-time localization under constrained-resources is a critical problem to be solved. In this paper, we present a new sparse pose-graph visual-inertial SLAM (SPVIS). Unlike the existing methods that are costly to deal with a large number of redundant features and 3D map points,…
In many applications of mobile robot, the environment is constantly changing. How to use historical information to analysis environmental changes and generate a map corresponding with current environment is important to achieve high-precision localization. Inspired by predictive mechanism of brain,…
With the advance in the field of mobile robots, autonomous robots are required for long-term deployment in dynamic and complex environments. However, the performance of Visual Inertial SLAM systems in long-term operation is not satisfactory, and most long-term SLAM systems assumes periodic changes i…