How Can a Robot Signal Its Incapability to Perform a Certain Task to Humans in an Acceptable Manner?

In this paper, a robot that is using politeness to overcome its incapability to serve is presented. The mobile robot “Alex” is interacting with human office colleagues in their environment and delivers messages, phone calls, and companionship. The robot's battery capacity is not sufficient to survive a full working day. Thus, the robot needs to recharge during the day. By doing so it is unavailable for tasks that involve movement. The study presented in this paper supports the idea that an incapability of fullfiling an appointed task can be overcome by politeness and showing appropriate behaviour. The results, reveal that, even the simple adjustment of spoken utterances towards a more polite phrasing can change the human's perception of the robot companion. This change in the perception can be made visible by analysing the human's behaviour towards the robot

Effects of automation on situation awareness in controlling robot teams

Declines in situation awareness (SA) often accompany automation. Some of these effects have been characterized as out-of-the-loop, complacency, and automation bias. Increasing autonomy in multi-robot control might be expected to produce similar declines in operators’ SA. In this paper we review a series of experiments in which automation is introduced in controlling robot teams. Automating path planning at a foraging task improved both target detection and localization which is closely tied to SA. Timing data, however, suggested small declines in SA for robot location and pose. Automation of image acquisition, by contrast, led to poorer localization. Findings are discussed and alternative explanations involving shifts in strategy proposed

Effects of alarms on control of robot teams

Annunciator driven supervisory control (ADSC) is a widely used technique for directing human attention to control systems otherwise beyond their capabilities. ADSC requires associating abnormal parameter values with alarms in such a way that operator attention can be directed toward the involved subsystems or conditions. This is hard to achieve in multirobot control because it is difficult to distinguish abnormal conditions for states of a robot team. For largely independent tasks such as foraging, however, self-reflection can serve as a basis for alerting the operator to abnormalities of individual robots. While the search for targets remains unalarmed the resulting system approximates ADSC. The described experiment compares a control condition in which operators perform a multirobot urban search and rescue (USAR) task without alarms with ADSC (freely annunciated) and with a decision aid that limits operator workload by showing only the top alarm. No differences were found in area searched or victims found, however, operators in the freely annunciated condition were faster in detecting both the annunciated failures and victims entering their cameras' fields of view. Copyright 2011 by Human Factors and Ergonomics Society, Inc. All rights reserved

Post-test questionnaire - HRI 1

This questionnaire has been used within the experiments described in a forthcoming publication in order to assess participants' conscious assessment of the quality of the interaction they have experienced with the robot. The questionnaire is based on two established questionnaires assessing participants' perception of `presence': the Temple Presence Inventory (TPI), and the Networked Minds Social Presence Inventory (NMI

The Proper Work of the Intellect

There is a familiar teleological picture of epistemic normativity on which it is grounded in the goal or good of belief, which is taken in turn to be the acquisition of truth and the avoidance of error. This traditional picture has faced numerous challenges, but one of the most interesting of these is an argument that rests on the nearly universally accepted view that this truth goal, as it is known, is at heart two distinct goals that are in tension with one another. This paper will look more closely at the standard way of understanding the truth goal, drawing out both its explicit and implicit features. My aim will be to show that this conception of the truth goal is deeply mistaken, to propose and defend an alternative model, and to show how this alternative model restores the unity of the goal and its potential to ground and explain the normative dimensions of belief

A robust extended H-infinity filtering approach to multi-robot cooperative localization in dynamic indoor environments

Multi-robot cooperative localization serves as an essential task for a team of mobile robots to work within an unknown environment. Based on the real-time laser scanning data interaction, a robust approach is proposed to obtain optimal multi-robot relative observations using the Metric-based Iterative Closest Point (MbICP) algorithm, which makes it possible to utilize the surrounding environment information directly instead of placing a localization-mark on the robots. To meet the demand of dealing with the inherent non-linearities existing in the multi-robot kinematic models and the relative observations, a robust extended H∞ filtering (REHF) approach is developed for the multi-robot cooperative localization system, which could handle non-Gaussian process and measurement noises with respect to robot navigation in unknown dynamic scenes. Compared with the conventional multi-robot localization system using extended Kalman filtering (EKF) approach, the proposed filtering algorithm is capable of providing superior performance in a dynamic indoor environment with outlier disturbances. Both numerical experiments and experiments conducted for the Pioneer3-DX robots show that the proposed localization scheme is effective in improving both the accuracy and reliability of the performance within a complex environment.This work was supported inpart by the National Natural Science Foundation of China under grants 61075094, 61035005 and 61134009

Development of an undergraduate multidisciplinary engineering project

During their time at university it is necessary for undergraduate engineering students to develop not just technical skills related to their chosen engineering subject, but to also develop team working, time management, self organisation and decision making skills that will enable them to work effectively as engineers in the real world after graduation. These important transferable skills are highly sought after by industry and any chance to identify where such skills have been successfully used during an undergraduate degree course is a valuable addition to a student’s CV when subsequently entering the job market. To address the need of developing transferable skills, the School of Engineering and Design Multidisciplinary Project (MDP) was introduced in 2007 to provide first year undergraduate students with an opportunity to work together in multidisciplinary teams on a design and construction project. Each team is comprised of students from across the range of subject areas within the School and tasked with designing and building a robotic vehicle to tackle an obstacle course. The basis for the kits provided to each team are Lego Mindstorms robots for a majority of groups while the remaining groups are provided with a Parallax Basic STAMP 2 chip and a micro-controller chip to design their vehicle around. Figure 1 shows a selection of the 50 completed project builds from the 2009 MDP, showing the wide array of designs produced by the students. This paper describes the main aims of the MDP and gives an overview of how it has developed over the last three years to become a key part of the engineering undergraduate programme at Brunel University

Effects of spatial ability on multi-robot control tasks

Working with large teams of robots is a very complex and demanding task for any operator and individual differences in spatial ability could significantly affect that performance. In the present study, we examine data from two earlier experiments to investigate the effects of ability for perspective-taking on performance at an urban search and rescue (USAR) task using a realistic simulation and alternate displays. We evaluated the participants' spatial ability using a standard measure of spatial orientation and examined the divergence of performance in accuracy and speed in locating victims, and perceived workload. Our findings show operators with higher spatial ability experienced less workload and marked victims more precisely. An interaction was found for the experimental image queue display for which participants with low spatial ability improved significantly in their accuracy in marking victims over the traditional streaming video display. Copyright 2011 by Human Factors and Ergonomics Society, Inc. All rights reserved

Real-Time Salient Closed Boundary Tracking via Line Segments Perceptual Grouping

This paper presents a novel real-time method for tracking salient closed boundaries from video image sequences. This method operates on a set of straight line segments that are produced by line detection. The tracking scheme is coherently integrated into a perceptual grouping framework in which the visual tracking problem is tackled by identifying a subset of these line segments and connecting them sequentially to form a closed boundary with the largest saliency and a certain similarity to the previous one. Specifically, we define a new tracking criterion which combines a grouping cost and an area similarity constraint. The proposed criterion makes the resulting boundary tracking more robust to local minima. To achieve real-time tracking performance, we use Delaunay Triangulation to build a graph model with the detected line segments and then reduce the tracking problem to finding the optimal cycle in this graph. This is solved by our newly proposed closed boundary candidates searching algorithm called "Bidirectional Shortest Path (BDSP)". The efficiency and robustness of the proposed method are tested on real video sequences as well as during a robot arm pouring experiment.Comment: 7 pages, 8 figures, The 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017) submission ID 103