Simultaneous localization and mapping (SLAM) is a fundamental problem in robotics and computer vision. It involves the task of a robot or an autonomous system navigating an unknown environment, simultaneously creating a map of the surroundings, and accurately estimating its position within that map. While significant progress has been made in SLAM over the years, challenges still need to be addressed. One prominent issue is robustness and accuracy in dynamic environments, which can cause uncertainties and errors in the estimation process. Traditional methods using temporal information to differentiate static and dynamic objects have limitations in accuracy and applicability. Nowadays, many research trends have leaned towards utilizing deep learning-based methods which leverage the capabilities to handle dynamic objects, semantic segmentation, and motion estimation, aiming to improve accuracy and adaptability in complex scenes. This article proposed an approach to enhance monocular visual odometry's robustness and precision in dynamic environments. An enhanced algorithm using the semantic segmentation algorithm DeeplabV3+ is used to identify dynamic objects in the image and then apply the motion consistency check to remove feature points belonging to dynamic objects. The remaining static feature points are then used for feature matching and pose estimation based on ORB-SLAM2 using the Technical University of Munich (TUM) dataset. Experimental results show that our method outperforms traditional visual odometry methods in accuracy and robustness, especially in dynamic environments. By eliminating the influence of moving objects, our method improves the accuracy and robustness of visual odometry in dynamic environments. Compared to the traditional ORB-SLAM2, the results show that the system significantly reduces the absolute trajectory error and the relative pose error in dynamic scenes. Our approach has significantly improved the accuracy and robustness of the SLAM system's pose estimation.
Understanding the genetic basis of population divergence and adaptation is an important goal in population genetics and evolutionary biology. However, the relative roles of demographic history, gene flow, and/or selective regime in driving genomic divergence, climatic adaptation, and speciation in non-model tree species are not yet fully understood. To address this issue, we generated whole-genome resequencing data of Liquidambar formosana and L. acalycina, which are broadly sympatric but altitudinally segregated in the Tertiary relict forests of subtropical China. We integrated genomic and environmental data to investigate the demographic history, genomic divergence, and climatic adaptation of these two sister species. We inferred a scenario of allopatric species divergence during the late Miocene, followed by secondary contact during the Holocene. We identified multiple genomic islands of elevated divergence that mainly evolved through divergence hitchhiking and recombination rate variation, likely fostered by long-term refugial isolation and recent differential introgression in low-recombination genomic regions. We also found some candidate genes with divergent selection signatures potentially involved in climatic adaptation and reproductive isolation. Our results contribute to a better understanding of how late Tertiary/Quaternary climatic change influenced speciation, genomic divergence, climatic adaptation, and introgressive hybridization in East Asia's Tertiary relict flora. In addition, they should facilitate future evolutionary, conservation genomics, and molecular breeding studies in Liquidambar, a genus of important medicinal and ornamental values.
Many insect pests, including the brown planthopper (BPH), undergo windborne migration that is challenging to observe and track. It remains controversial about their migration patterns and largely unknown regarding the underlying genetic basis. By analyzing 360 whole genomes from around the globe, we clarify the genetic sources of worldwide BPHs and illuminate a landscape of BPH migration showing that East Asian populations perform closed-circuit journeys between Indochina and the Far East, while populations of Malay Archipelago and South Asia undergo one-way migration to Indochina. We further find round-trip migration accelerates population differentiation, with highly diverged regions enriching in a gene desert chromosome that is simultaneously the speciation hotspot between BPH and related species. This study not only shows the power of applying genomic approaches to demystify the migration in windborne migrants but also enhances our understanding of how seasonal movements affect speciation and evolution in insects.