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January 17, 2023
This dissertation explores distributed algorithms for calibration, localisation, and mapping in the context of a multi-robot network equipped with cameras and onboard processing, comparing against centralised alternatives where all data is transmitted to a singular external node on which processing occurs. With the rise of large-scale camera networks, and as low-cost on-board processing becomes increasingly feasible in robotics networks, distributed algorithms are becoming important for robustne...
June 3, 2022
San Francisco, 05/27/22 (PRWEB) May 31, 2022 -- The new Neural Depth mode generates a dense, high-fidelity depth map up to 2k resolution. The map is able to
April 16, 2021
Abstract Existing unsupervised visual odometry (VO) methods either match pairwise images or integrate the temporal information using recurrent neural networks over a long sequence of images. They are either not accurate, time-consuming in training or error accumulative. In this paper, we propose a method consisting of two camera pose estimators that deal with the information from pairwise images and a short sequence of images, respectively. For image sequences, a transformer-like structure is a...