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In recent years, a low-cost range sensing technology (such as Kinect) has attracted many researchers in vision community. Despite being promising for indoor navigation, continuous operation in a challenging environments is still a fundamental problem. This paper presents a real-time approach of combining range-color (RGB-D) cues with inertial information in a loosely-coupled framework for Simultaneous...
Monocular visual SLAM approaches are mostly constrained in their performance due to general motion model and availability of true scale information. We proposed an approach which improves the motion prediction step of visual SLAM and results in better estimation of map scale. The approach utilizes the short term accuracy of inertial velocity with visual orientation to estimate refined motion priors...
This paper presents Sparse Depth Odometry (SDO) to incrementally estimate the 3D pose of a depth camera in indoor environments. SDO relies on 3D keypoints extracted on dense depth data and hence can be used to augment the RGB-D camera based visual odometry methods that fail in places where there is no proper illumination. In SDO, our main contribution is the design of the keypoint detection module,...
Online and robust localization in a large scale outdoor environment is an essential component for self-driving vehicles. This paper addresses the theoretical and experimental development of a 6DOF localization approach with an online Unscented Rauch-Tung-Striebel (RTS) Smoother. This work focuses on the performance evaluation of the Unscented RTS smoother from a low-cost inertial sensor and consumer-grade...
Recently, the robotics community has widely used color-depth (RGB-D) sensors for various applications, such as collision avoidance, navigation and robotic path planning. To effectively utilize the benefit of depth and color modalities, it is important to know the relative pose between these sensors. In this paper we proposed a theoretical and practical approach to estimate the rigid body transformation...
Three dimensional Simultaneous Localization and Mapping (SLAM) is one of the fundamental task for autonomous robots, to operate successfully in unknown environment. Recently convexity analysis for 2D mobile-robot SLAM system has been analyzed whereas for highly nonlinear problems i.e. 3D SLAM for aerial robotic, the understanding of convex structure of the system is much of interest to robotics community...
Inertial-SLAM has been actively studied as it can provide all-terrain navigational capability with full six degrees-of-freedom information to autonomous robots. With the recent availability of low-cost inertial and vision sensors, a light-weight and accurate mapping system could be achieved for many robotic tasks such as land/aerial explorations. The key challenge toward this is in the availability...
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