Demo Data from VLDB 2026 / reviewers in the wild / expert
Andrew J. McDaid
dblp:134/9210 · also Andrew McDaid
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2020
0000-0003-3316-7344ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 3Artificial intelligence and machine learning · 2Applied, interdisciplinary, general and emerging computing · 2
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Human-robot interaction · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computing education · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction
social robot |
0.4 | 1 | 2019 | Teaching Social Robotics to Motivate Women into Engineering and Robotics Careers · HRI 2019 |
Human-robot interaction › educational robotics
social robots in education |
0.4 | 1 | 2019 | Teaching Social Robotics to Motivate Women into Engineering and Robotics Careers · HRI 2019 |
Computing education
broadening participation in computing |
0.1 | 1 | 2019 | Teaching Social Robotics to Motivate Women into Engineering and Robotics Careers · HRI 2019 |
Methods — techniques the papers use, named apart from their topics
questionnaire · 0.8observation · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Synchronous Position and Compliance Regulation on a Bi-Joint Gait Exoskeleton Driven by Pneumatic MusclesabstractA previously developed pneumatic muscles' (PMs) actuated gait exoskeleton (with only knee joint) has been demonstrated in achieving appropriate actuation torque, range of motion (ROM), and control bandwidth for task-specific gait training. While the adopted multi-input-multi-output (MIMO) sliding mode (SM) strategy has preliminarily implemented simultaneous control of the exoskeleton's angular trajectory and compliance, its efficacy with human users during gait cycles has not been investigated. This article presents an improved bi-joint gait rehabilitation exoskeleton (BiGREX) with integrated human hip and knee joints. The results with 12 healthy subjects demonstrated that the system's compliance can be effectively adjusted while guiding the subjects walking in predefined trajectories. Bin Zhong, Jinghui Cao, Andrew J. McDaid, Shengquan Xie, Mingming Zhang 0001 |
IEEE Trans Autom. Sci. Eng. | 3 |
| 2019 | Teaching Social Robotics to Motivate Women into Engineering and Robotics CareersabstractWomen are underrepresented in robotics, and this may be partly due to the educational emphasis on mechanical applications rather than social applications of robotics. This study aimed to investigate whether teaching robotics using social robots increased girls' engagement compared to using more mechanical vex robots. 20 girls were recruited from school robotics classes. They were taught 30 minutes of VEX robotics and 30 minutes of social robotics in a counter-balanced order. Engagement was measured using questionnaires and observations. Results showed that girls were significantly more engaged in the social robot classes than the vex robot classes. This pilot study suggests a possible way to encourage more girls to study robotics. Alex Barco, Rhea Montgomery Walsh, Avram Block, Kate Loveys, Andrew J. McDaid, Elizabeth Broadbent |
HRI | 5 |
| 2017 | How Can Adding a Movement Improve Target Acquisition Efficacy?
Alexander R. Payne, Beryl Plimmer, Andrew J. McDaid, Andrew Luxton-Reilly, Theresa Claire Davies |
INTERACT (3) | 3 |
| 2016 | User perceptions of soft robot arms and fingers for healthcareabstractSafety and acceptability are critical issues when people are interacting with robots in healthcare. Traditional robot arms are hard and inflexible, and may cause harm to users on impact. Soft robotic arms may be safer and more acceptable in these situations. Similarly robot fingers made of soft materials may be more acceptable and safer than fingers made of hard materials. Robot designers need to know how best to design arms for healthcare scenarios. There is limited research on the acceptability of soft robotic arms and fingers to date. This study aimed to investigate people's reactions to the touch of soft robotic arms and fingers, compared to more traditional hard forms, and to human arms and fingers. A second aim was to investigate people's perceptions of the usefulness of the arms and fingers for healthcare tasks. Thirty five community participants were blindfolded and participated in touching tasks for: 3 arms (soft robot, hard robot, and human) and four fingers (soft robot, medium robot, hard robot, and human) in a randomised order. The soft arm was rated significantly more human-like but also more fragile and less reliable than the hard arm. Participants perceived the soft arm as good for intimate tasks like washing the body, but the hard arm was perceived as better for weight-bearing tasks. The soft finger was rated significantly more creepy, fragile and unreliable than the other fingers. The medium robot finger was rated the most human-like of the robot fingers and was the favourite robot finger. These findings suggest people perceive soft robots to be more fragile than hard robots and as more appropriate for personal tasks. Overly soft fingers may be too creepy to be acceptable. Bruce A. MacDonald, Andrew J. McDaid, Sadao Kawamura, Hye-Jong Kim, Elliot Thompson Bean, Forest Fraser, Elizabeth Broadbent |
RO-MAN | 3 |