Autonomous visual-inertial navigation and absolute visual scale estimation

In this thesis, we present a system that uses a single camera and an inertial measurement unit (IMU) to navigate an Unmanned Aerial Vehicle (UAV) in a previously unknown environment. The approach consists of two parts. First, we apply a state-of-the-art simultaneous localization and mapping (SLAM) method to the video stream of a onboard camera. From the SLAM system, an up-to-a-scale pose of the camera is estimated, because the absolute size of the environment cannot be estimated with a single camera. Second, the estimated pose is fused with the data from IMU to resolve the scale ambiguity. While analyzing the performance of the system, we find that the conver- gence rate of scale decreases when the magnitude of scale increases. This relationship has not been demonstrated and explained before. In this thesis, we present an analysis and explanation of this phenomenon

Self-supervised 6D Object Pose Estimation for Robot Manipulation

To teach robots skills, it is crucial to obtain data with supervision. Since annotating real world data is time-consuming and expensive, enabling robots to learn in a self-supervised way is important. In this work, we introduce a robot system for self-supervised 6D object pose estimation. Starting from modules trained in simulation, our system is able to label real world images with accurate 6D object poses for self-supervised learning. In addition, the robot interacts with objects in the environment to change the object configuration by grasping or pushing objects. In this way, our system is able to continuously collect data and improve its pose estimation modules. We show that the self-supervised learning improves object segmentation and 6D pose estimation performance, and consequently enables the system to grasp objects more reliably. A video showing the experiments can be found at https://youtu.be/W1Y0Mmh1Gd8.Comment: Accepted to International Conference on Robotics and Automation (ICRA), 202

Moisture content effects on self-heating in stored biomass: An experimental study

Biomass is essential for modern bioenergy applications, but long-term storage of large volumes of it can pose challenges to plant safety due to the intrinsic self-heating characteristics of biomass piles. In recent years, serious fire accidents have occurred because of self-heating. However, little research has been conducted on this concern. The effects of different initial moisture contents (range of 20–95 %) on the self-heating characteristics of rice and wheat straw, which are two different agricultural biomass residues, are investigated in this study. Biomass samples with different initial moisture contents are stored in a well-insulated container, and the temperature and oxygen levels within the stored biomass samples are monitored. Based on the tests, the heat production rate, oxygen consumption rate and microorganism growth rate are derived, and the impacts of the initial moisture contents on the self-heating characteristics of the stored biomass samples are analysed. The highest temperatures in the stored rice straw and wheat straw are attained under initial moisture contents of 50 % and 20 %, respectively, while the largest heat production rates for both straw types are attained under an initial moisture content of 95 %. An increase in the initial moisture content greatly enhances the overall biological reactivity and oxygen consumption rate. The heat production and oxygen consumption levels exhibit a clear positive correlation. Under identical storage conditions, wheat straw is more susceptible to self-heating than rice straw, as shown by its higher heat generation, faster oxygen consumption, and shorter temperature peaking time. This study contributes to a quantitative understanding of the underlying processes and provides valuable experimental data for model development to guide safe biomass storage systems.</p

Anion Exchange in Semiconductor Magic-Size Clusters

Ion exchange is an effective postsynthesis strategy for the design of colloidal nanomaterials with unique structures and properties. In contrast to the rapid development of cation exchange (CE), the study of anion exchange is still in its infancy and requires an in-depth understanding. Magic-size clusters (MSCs) are important reaction intermediates in quantum dot (QD) synthesis, and studying the ion exchange processes can provide valuable insights into the transformations of QDs. Here, we achieved anion exchange in Cd-based MSCs and elucidated the reaction pathways. We demonstrated that the anion exchange was a stepwise intermolecular transition mediated by covalent inorganic complexes (CICs). We proposed that this transition involved three essential steps: the disassembly of CdE1-MSCs into CdE1-CICs (step 1), an anion exchange reaction from CdE1-CICs to CdE2-CICs (step 2), and assembly of CdE2-CICs to CdE2-MSCs (step 3). Step 3 was the rate-determining step and followed first-order reaction kinetics (kobs = 0.01 min–1; from CdSe-MSCs to CdS-MSCs). Further studies revealed that the activity of foreign anions only affected the reaction kinetics without altering the reaction pathway. The present study provides a deeper insight into the anion exchange mechanisms of MSCs and will further shed light on the synthesis of QDs

Alterations of milk oligosaccharides in mothers with gestational diabetes mellitus impede colonization of beneficial bacteria and development of RORγt+ Treg cell-mediated immune tolerance in neonates

ABSTRACTGestational diabetes mellitus (GDM) is an increasing public health concern that significantly increases the risk of early childhood allergic diseases. Altered maternal milk glycobiome may strongly affect gut microbiota and enteric-specific Treg cell-mediated development of immune tolerance in GDM infants. In this study, we found that, compared with healthy Chinese mothers, mothers with GDM had significantly lower levels of total and specific human milk oligosaccharides (HMOs) in their colostrum that subsequently increased with extension of lactation. This alteration in HMO profiles significantly delayed colonization of Lactobacillus and Bifidobacterium spp. in their breast-fed infants, resulting in a distinct gut microbial structure and metabolome. Further experiments in GDM mouse models indicated that decreased contents of milk oligosaccharides, mainly 3ʹ-sialyllactose (3ʹ-SL), in GDM maternal mice reduced colonization of bacteria, such as L. reuteri and L. johnsonii, in the neonatal gut, which impeded development of RORγt+ regulatory T (Treg) cell-mediated immune tolerance. Treatment of GDM neonates with 3ʹ-SL, Lactobacillus reuteri (L. reuteri) and L. johnsonii promoted the proliferation of enteric Treg cells and expression of transcription factor RORγt, which may have contributed to compromising ovalbumin (OVA)-induced allergic responses. In vitro experiments showed that 3ʹ-SL, metabolites of L. johnsonii, and lysates of L. reuteri stimulated differentiation of mouse RORγt+ Treg cells through multiple regulatory effects on Toll-like receptor, MAPK, p53, and NOD-like receptor signaling pathways. This study provides new ideas for the development of gut microbiota and immune tolerance in GDM newborns