How does peoples’ perception of control depend on the criticality of a task performed by a robot Paladyn

© 2019 Adeline Chanseau et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution 4.0 Public License.Robot companions are starting to become more common and people are becoming more familiar with devices such as Google Home, Alexa or Pepper,one must wonder what is the optimum way for people to control their devices? This paper provides presents an investigation into how much direct control people want to have of their robot companion and how dependent this is on the criticality of the tasks the robot performs. A live experiment was conducted in the University of Hertfordshire Robot House, with a robot companion performing four different type of tasks. The four tasks were: booking a doctor’s appointment, helping the user to build a Lego character, doing a dance with the user, and carrying biscuits for the user. The selection of these tasks was based on our previous research to define tasks which were relatively high and low in criticality. The main goal of the study was to find what level of direct control over their robot participants and if this was dependent on the criticality of the task performed by the robot. Fifty people took part in the study, and each experienced every task in a random order. Overall,it was found that participants’ perception of control was higher when the robot was performing a task in a semi-autonomous mode. However, for the task "carrying biscuits", although participants perceived to be more in control with the robot performing the task in a semi autonomous mode, they actually preferred to have the robot performing the task automatically (where they felt less in control). The results also show that, for the task "booking a doctor’s appointment", considered to be the most critical of all four tasks, participants did not prefer that the robot chose the date of the appointment as they felt infantilised.Peer reviewe

Focusing on the Few: the Role of Large Taxpayer Units in the Revenue Strategies of Developing Countries

Part I of this paper first reviews the spread of LTUs, and briefly describes the experience of LTUs in a few selected countries. This section takes up the question of the LTU as an enclave administrative reform versus semi-autonomous revenue agencies and "whole of government" reform involving broad based wages, human resources planning and anti-corruption measures.Part II examines the emergence of the LTU and its relationships to the remainder of the tax administration system in different kinds of developing and transition economies, such as (i)capable developing states, (ii) administratively weak but governance improving states, and (iii)captured states. The relative success of LTUs can improve our understanding of the enclave approach to governance reforms as well as yielding insights that are intrinsic to the challenge of improving revenue mobilization. LTUs and their roles in developing country economies can also be interpreted through the prism of recent revisionist writings on best policies for the tax mix in the presence of a major informal sector and a government sector with a highly constrained taxing capacity and high vulnerability to corruption.Working Paper Number 04-44

A Synergistic Approach for Recovering Occlusion-Free Textured 3D Maps of Urban Facades from Heterogeneous Cartographic Data

In this paper we present a practical approach for generating an occlusion-free textured 3D map of urban facades by the synergistic use of terrestrial images, 3D point clouds and area-based information. Particularly in dense urban environments, the high presence of urban objects in front of the facades causes significant difficulties for several stages in computational building modeling. Major challenges lie on the one hand in extracting complete 3D facade quadrilateral delimitations and on the other hand in generating occlusion-free facade textures. For these reasons, we describe a straightforward approach for completing and recovering facade geometry and textures by exploiting the data complementarity of terrestrial multi-source imagery and area-based information

Vision-model-based Real-time Localization of Unmanned Aerial Vehicle for Autonomous Structure Inspection under GPS-denied Environment

UAVs have been widely used in visual inspections of buildings, bridges and other structures. In either outdoor autonomous or semi-autonomous flights missions strong GPS signal is vital for UAV to locate its own positions. However, strong GPS signal is not always available, and it can degrade or fully loss underneath large structures or close to power lines, which can cause serious control issues or even UAV crashes. Such limitations highly restricted the applications of UAV as a routine inspection tool in various domains. In this paper a vision-model-based real-time self-positioning method is proposed to support autonomous aerial inspection without the need of GPS support. Compared to other localization methods that requires additional onboard sensors, the proposed method uses a single camera to continuously estimate the inflight poses of UAV. Each step of the proposed method is discussed in detail, and its performance is tested through an indoor test case.Comment: 8 pages, 5 figures, submitted to i3ce 201