5 accepted papers
Robust and accurate localization technologies are crucial for autonomous vehicles and mobile robots. Precisely perceiving the 3D environment and its semantic attributes in the real world greatly enhances the ability of these systems to perform localization tasks effectively. This paper proposes GS-L
This paper is concerned with the motion control problem of an aerial manipulator that consists of a quadrotor base and a manipulator. We propose a novel control strategy that incorporates a simplified model considering the critical dynamics, and a linear-MPC-based trajectory converter to ensure prec
Implicit neural representation and explicit 3D Gaussian Splatting (3D-GS) for novel view synthesis have achieved remarkable progress with frame-based camera (e.g. RGB and RGB-D cameras) recently. Compared to frame-based camera, a novel type of bio-inspired visual sensor, i.e. event camera, has demon…
[1] Visual Simultaneous Localization and Mapping (SLAM) helps robots estimate their poses and perceive the environment in unknown settings. Recent work has demonstrated that implicit neural radiance fields and 3D Gaussian Splatting (3DGS) offer higher fidelity scene representation than traditional m
Recent advancements in neural implicit fields for Simultaneous Localization and Mapping (SLAM) have provided breakthroughs. However, the benefits of reconstruction results to the perception ability of robot are minimal. Therefore, we propose FI-SLAM, a dense semantic instance SLAM system based on ne…