Epochal Challenges: the Robotic Revelation in Anthropology

In this technological epoch, the development of cyborgs and robots has affected perceptions inside and outside anthropology as a new thinking model of knowledge construction. Moore (2003: 7) asserts that ‘science and technology are transforming anthropological knowledge through a transformation of its objects of enquiry’. The robotic technology has posed potential threats as well as brought new hopes to the field of anthropology. This essay illustrates both sides in terms of three anthropological topics—(i) identity; (ii) family structures and values; and (iii) religion. Through analysis, it shows the importance of reducing risks through regulations, seizing opportunities through rethinking old concepts and applying new techniques to the existing knowledge. Moreover, a pioneering spirit is called to face challenges and to make contributions for humanity’s sake

Adelic line bundles over quasi-projective varieties

In this paper, we establish a theory of adelic line bundles over quasi-projective varieties over finitely generated fields. Besides definitions of adelic line bundles, we consider their intersection theory, volume theory, and height theory, and apply these to study heights of algebraic points of quasi-projective varieties.Comment: 224 page

Cross-domain Few-shot Segmentation with Transductive Fine-tuning

Few-shot segmentation (FSS) expects models trained on base classes to work on novel classes with the help of a few support images. However, when there exists a domain gap between the base and novel classes, the state-of-the-art FSS methods may even fail to segment simple objects. To improve their performance on unseen domains, we propose to transductively fine-tune the base model on a set of query images under the few-shot setting, where the core idea is to implicitly guide the segmentation of query images using support labels. Although different images are not directly comparable, their class-wise prototypes are desired to be aligned in the feature space. By aligning query and support prototypes with an uncertainty-aware contrastive loss, and using a supervised cross-entropy loss and an unsupervised boundary loss as regularizations, our method could generalize the base model to the target domain without additional labels. We conduct extensive experiments under various cross-domain settings of natural, remote sensing, and medical images. The results show that our method could consistently and significantly improve the performance of prototypical FSS models in all cross-domain tasks.Comment: 12 pages, 8 figure

Fast forward: technography of the social integration of connected and automated vehicles into UK society

The emerging connected and automated vehicles (CAV) have caught much research attention in the past few years. However, a techno-centric bias in the CAV research domain implies the lack of in-depth qualitative studies. To fill the gap, this Ph.D. project bridges the fields of Social Anthropology with STS by adopting technography, an ethnography of technology, to enable a thick description of the CAV technology’s social integration into UK society. By critically drawing a holistic view of the ongoing process of the CAV social deployment, it aims to (1) unfold CAV’s potential problems and dynamic contributions to everyday life through the lens of sociotechnical imaginaries, and (2) reveal and analyse the institutional practice on its social rollout. Based on pilot research and one-year-long fieldwork in London and Edinburgh, the thesis investigated a wide range of important socio-political aspects where fundamental topics such as trust, human-and-machine relationship, social safety, political transparency, and equity in transport systems were explicated. Different from the planners’ top-down CAV imaginaries that focused on its contribution to functional safety, environment, and the economy, the public’s bottom-up imaginaries highlighted issues that were related to their travelling experiences, such as inequity of transport service distribution and sexual harassment during commutes. These findings inspired thinking and rethinking on what constitutes the success of technology’s social deployment from multiple perspectives. In particular, it critically pointed out that safety means not only technological feasibility but also social safety that refers to a safe commuting environments. Such finding in my thesis thus suggests that CAV technology is not a one-size-fits-all solution to problems in our transport system and calls for research effort to the broader socio-political and ethical areas of this technology. through an investigation of the institutional practice, it identified four major institutional forces, including technicians, industry stakeholders, researchers, and policymakers who have been working on these aspects with different approaches and priorities. Apart from acknowledging their efforts in building safety cases, pushing forward the CAV legislation, and engaging the public in trials, it critically explained challenges such as technical uncertainty and political tension in developing and implementing a legal framework. Hence, the project contributes to an understanding of a close encounter between the CAV technology and its imaginaries, in which, technical and socio-political problems and potentials fabricate the richness in its social deployment. It also explicates the importance of embracing multiple perspectives and calls for continuous research in this field

Robust Position-based Visual Servoing of Industrial Robots

Recently, the researchers have tried to use dynamic pose correction methods to improve the accuracy of industrial robots. The application of dynamic path tracking aims at adjusting the end-effector’s pose by using a photogrammetry sensor and eye-to-hand PBVS scheme. In this study, the research aims to enhance the accuracy of industrial robot by designing a chattering-free digital sliding mode controller integrated with a novel adaptive robust Kalman filter (ARKF) validated on Puma 560 model on simulation. This study includes Gaussian noise generation, pose estimation, design of adaptive robust Kalman filter, and design of chattering-free sliding mode controller. The designed control strategy has been validated and compared with other control strategies in Matlab 2018a Simulink on a 64bits PC computer. The main contributions of the research work are summarized as follows. First, the noise removal in the pose estimation is carried out by the novel ARKF. The proposed ARKF deals with experimental noise generated from photogrammetry observation sensor C-track 780. It exploits the advantages of adaptive estimation method for states noise covariance (Q), least square identification for measurement noise covariance (R) and a robust mechanism for state variables error covariance (P). The Gaussian noise generation is based on the collected data from the C-track when the robot is in a stationary status. A novel method for estimating covariance matrix R considering both effects of the velocity and pose is suggested. Next, a robust PBVS approach for industrial robots based on fast discrete sliding mode controller (FDSMC) and ARKF is proposed. The FDSMC takes advantage of a nonlinear reaching law which results in faster and more accurate trajectory tracking compared to standard DSMC. Substituting the switching function with a continuous nonlinear reaching law leads to a continuous output and thus eliminating the chattering. Additionally, the sliding surface dynamics is considered to be a nonlinear one, which results in increasing the convergence speed and accuracy. Finally, the analysis techniques related to various types of sliding mode controller have been used for comparison. Also, the kinematic and dynamic models with revolutionary joints for Puma 560 are built for simulation validation. Based on the computed indicators results, it is proven that after tuning the parameters of designed controller, the chattering-free FDSMC integrated with ARKF can essentially reduce the effect of uncertainties on robot dynamic model and improve the tracking accuracy of the 6 degree-of-freedom (DOF) robot