Jesse Clark is a software engineer who has built distributed systems for a number of Silicon Valley startups. At NASA he developed databases for the International Space Station and robotic simulations for the Hubble Space Telescope.
Gardenfors, P, Williams, M-A, Johnston, B, Billingsley, R, Vitale, J, Peppas, P & Clark, J 2018, 'Event boards as tools for holistic AI', International Workshop on Artificial Intelligence and Cognition 2018, Palermo, Italy.View/Download from: UTS OPUS
Vitale, J, Tonkin, M, Herse, S, Ojha, S, Clark, J, Williams, M, Wang, X & Judge, W 2018, 'Be More Transparent and Users Will Like You: A Robot Privacy and User Experience Design Experiment', Proceedings of 2018 ACM/IEEE International Conference on Human- Robot Interaction, International Conference on Human-Robot Interaction, ACM, Chicago, IL, USA, pp. 379-387.View/Download from: UTS OPUS or Publisher's site
Herse, S, Vitale, J, Ebrahimian, D, Tonkin, M, Ojha, S, Sidra, S, Johnston, B, Phillips, S, Gudi, SLKC, Clark, J, Judge, W & Williams, MA 2018, 'Bon Appetit! Robot Persuasion for Food Recommendation', ACM/IEEE International Conference on Human-Robot Interaction, ACM/IEEE International Conference on Human-Robot Interaction, ACM, Chicago, USA, pp. 125-126.View/Download from: UTS OPUS or Publisher's site
© 2018 Authors. The integration of social robots within service industries requires social robots to be persuasive. We conducted a vignette experiment to investigate the persuasiveness of a human, robot, and an information kiosk when offering consumers a restaurant recommendation. We found that embodiment type significantly affects the persuasiveness of the agent, but only when using a specific recommendation sentence. These preliminary results suggest that human-like features of an agent may serve to boost persuasion in recommendation systems. However, the extent of the effect is determined by the nature of the given recommendation.
Krishna Chand Gudi, SL, Ojha, S, Johnston, B, Clark, J & Williams, MA 2018, 'Fog robotics for efficient, fluent and robust human-robot interaction', NCA 2018 - 2018 IEEE 17th International Symposium on Network Computing and Applications, International Symposium on Network Computing and Applications, IEEE, Cambridge, MA, USA.View/Download from: UTS OPUS or Publisher's site
© 2018 IEEE. Active communication between robots and humans is essential for effective human-robot interaction. To accomplish this objective, Cloud Robotics (CR) was introduced to make robots enhance their capabilities. It enables robots to perform extensive computations in the cloud by sharing their outcomes. Outcomes include maps, images, processing power, data, activities, and other robot resources. But due to the colossal growth of data and traffic, CR suffers from serious latency issues. Therefore, it is unlikely to scale a large number of robots particularly in human-robot interaction scenarios, where responsiveness is paramount. Furthermore, other issues related to security such as privacy breaches and ransomware attacks can increase. To address these problems, in this paper, we have envisioned the next generation of social robotic architectures based on Fog Robotics (FR) that inherits the strengths of Fog Computing to augment the future social robotic systems. These new architectures can escalate the dexterity of robots by shoving the data closer to the robot. Additionally, they can ensure that human-robot interaction is more responsive by resolving the problems of CR. Moreover, experimental results are further discussed by considering a scenario of FR and latency as a primary factor comparing to CR models.
Tonkin, M, Vitale, J, Ojha, S, Clark, J, Pfeiffer, S, Judge, W, Wang, X & Williams, M 2017, 'Embodiment, Privacy and Social Robots: May I Remember You?', Social Robotics: 9th International Conference, ICSR 2017, International Conference on Social Robotics, Springer International Publishing, Tsukuba, Japan, pp. 506-515.View/Download from: UTS OPUS or Publisher's site
As social robots move from the laboratory into public settings the possibility of unwanted intrusion into a user's personal privacy is magnified.
The actual social interaction between human and robot may involve anthropomorphising of the robot by the user, and this may prompt the user to disclose private or sensitive information. To comprehend possible impacts we conducted an exploratory study with a novel privacy measure to understand changes to users' privacy considerations when interacting with an embodied robotic system vs a disembodied system.
In this paper we measure the difference in personal information provided to such systems, and discuss the idea that embodiment may increase users' risk tolerance and reduce their privacy concerns.
Cloud Robotics (CR) is an emerging and successful approach to robotics. The number of robots or other IoT
devices may increase drastically in the future which might need
enormous bandwidth and there might be security concerns. If
robots in CR are not secured then robots can even become
surveillance bot by hackers. Moreover, if an internet connection
is lost due to network hitches then in that crucial moment robot
may not be available to complete its given task. For example,
a robot assisting a person can stop working unexpectedly or
work with the instructions from hacker. In order to address
such problems, we propose a new approach to robotics - Fog
Robotics (FR) in this paper, so a network of robots can be used
more securely and efficiently as compared to CR.