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This paper proposes a pose-based GraphSLAM algorithm for robotic fish equipped with a Mechanical Scanning Sonar (MSS) that has a low frequency of range readings. The main contribution of this paper is the construction of a pose graph as the front-end part of the normal GraphSLAM algorithm. The proposed algorithm has three stages as follows: 1) scan generation which incorporates a novel Extended Kalman...
We consider the task of long-term visual SLAM, i.e., simultaneous localization and mapping, in a partially changing environment (SLAM-PCE). The main problem we face is how to obtain discriminative and compact visual landmarks, which are necessary to cope with changes in appearance in an environment and with a large amount of visual information. We address this issue by proposing the use of common...
This paper proposes a new approach of monocular ceiling vision based simultaneous localization and mapping (SLAM) by utilizing an improved Square Root Unscented Kalman Filter (SRUKF). With a monocular camera mounted on the top of a mobile robot and looking upward to the ceiling, the robot only needs to process salient features, which greatly reduce the computational complexity and have a high accuracy...
This paper proposes a novel FastSLAM based on UT (Unscented Transform). A novel proposal distribution which integrates current observation is proposed, wherein the particles sampled from the proposal distribution based on Unscented Transform is driven to move to the high probability region of posterior distribution. The landmarks in map are updated with UKF (Unscented Kalman Filter) to avoid the problem...
In this paper, we investigate the effects of including disparity as an explicit measurement (not just for initialization) in addition to the projective camera measurements, in conventional monocular/bearing-only SLAM in a 2-D world. We conduct an observability analysis for a 1.5-D scenario which theoretically shows that adding disparity measurements influences the observability rank condition, and...
This paper describes an efficient SLAM system only using RGBD sensors. This system utilizes the Microsoft Kinects to provide visual odometry estimation and 2D range scans. The Kinect looking up toward the ceiling can track the robot's trajectory through visual odometry method, which can provide more accurate motion estimation compared to wheel motion measurement and cannot be disturbed under wheel...
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...
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