Crowd of oz : A crowd-powered social robotics system for stress management

Coping with stress is crucial for a healthy lifestyle. In the past, a great deal of research has been conducted to use socially assistive robots as a therapy to alleviate stress and anxiety related problems. However, building a fully autonomous social robot which can deliver psycho-therapeutic solutions is a very challenging endeavor due to limitations in artificial intelligence (AI). To overcome AI’s limitations, researchers have previously introduced crowdsourcing-based teleoperation methods, which summon the crowd’s input to control a robot’s functions. However, in the context of robotics, such methods have only been used to support the object manipulation, navigational, and training tasks. It is not yet known how to leverage real-time crowdsourcing (RTC) to process complex therapeutic conversational tasks for social robotics. To fill this gap, we developed Crowd of Oz (CoZ), an open-source system that allows Softbank’s Pepper robot to support such conversational tasks. To demonstrate the potential implications of this crowd-powered approach, we investigated how effectively, crowd workers recruited in real-time can teleoperate the robot’s speech, in situations when the robot needs to act as a life coach. We systematically varied the number of workers who simultaneously handle the speech of the robot (N = 1, 2, 4, 8) and investigated the concomitant effects for enabling RTC for social robotics. Additionally, we present Pavilion, a novel and open-source algorithm for managing the workers’ queue so that a required number of workers are engaged or waiting. Based on our findings, we discuss salient parameters that such crowd-powered systems must adhere to, so as to enhance their performance in response latency and dialogue quality. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

Remote interaction with mobile robots

This paper describes an architecture, which can be used to build remote laboratories to interact remotely via Internet with mobile robots using different interaction devices. A supervisory control strategy has been used to develop the remote laboratory in order to alleviate high communication data rates and system sensitivity to network delays. The users interact with the remote system at a more abstract level using high level commands. The local robot's autonomy has been increased by encapsulating all the robot's behaviors in different types of skills. User interfaces have been designed using visual proxy pattern to facilitate any future extension or code reuse. The developed remote laboratory has been integrated into an educational environment in the field of indoor mobile robotics. This environment is currently being used as a part of an international project to develop a distributed laboratory for autonomous and teleoperated systems (IECAT, 2003).Publicad

Human-Machine Interfaces for Service Robotics

L'abstract è presente nell'allegato / the abstract is in the attachmen

Evaluation of teleoperation system performance over a cellular network

The ubiquity of cellular networks has exploded over the last half decade making internet access a given when located in an urban settings. On top of this, new technologies like 4G LTE provide higher transfer speeds than ever, permitting streaming of video and other high bandwidth services. Though cellular networks are not new, few studies have leveraged this particular communications method when studying teleoperations, due to the significant bandwidth restrictions. As a result, this study seeks to understand whether teleoperation could be implemented over regular cellular networks where the bandwidth load that each cell tower is subject to cannot be controlled by the teleoperation system. For this, a prototype system is built using a remote controlled golf cart that hosts a multimedia link between the vehicle and a control station which communicate over the internet. The system is tested by measuring teleoperation for 3 different tasks of varying degrees of complexity. The results reveal that latency can be low enough to optimally control a remote vehicle. Nevertheless, the performance greatly depends on the network conditions that can vary significantly. The results also indicated that in-situ driving outperformed remote operation.M.S

On-Demand Collaboration in Programming

In programming, on-demand assistance occurs when developers seek support for their tasks as needed. Traditionally, this collaboration happens within teams and organizations in which people are familiar with the context of requests and tasks. More recently, this type of collaboration has become ubiquitous outside of teams and organizations, due to the success of paid online crowdsourcing marketplaces (e.g., Upwork) and free online question-answering websites (e.g., Stack Overflow). Thousands of requests are posted on these platforms on a daily basis, and many of them are not addressed in a timely manner for a variety of reasons, including requests that often lack sufficient context and access to relevant artifacts. In consequence, on-demand collaboration often results in suboptimal productivity and unsatisfactory user experiences. This dissertation includes three main parts: First, I explored the challenges developers face when requesting help from or providing assistance to others on demand. I have found seven common types of requests (e.g., seeking code examples) that developers use in various projects when an on-demand agent is available. Compared to studying existing supporting systems, I suggest eight key system features to enable more effective on-demand remote assistance for developers. Second, driven by these findings, I designed and developed two systems: 1) CodeOn, a system that enables more effective task hand-offs (e.g., rich context capturing) between end-user developers and remote helpers than exciting synchronous support systems by allowing asynchronous responses to on-demand requests; and 2) CoCapture, a system that enables interface designers to easily create and then accurately describe UI behavior mockups, including changes they want to propose or questions they want to ask about an aspect of the existing UI. Third, beyond software development assistance, I also studied intelligent assistance for embedded system development (e.g., Arduino) and revealed six challenges (e.g., communication setup remains tedious) that developers have during on-demand collaboration. Through an imaginary study, I propose four design implications to help develop future support systems with embedded system development. This thesis envisions a future in which developers in all kinds of domains can effortlessly make context-rich, on-demand requests at any stage of their development processes, and qualified agents (machine or human) can quickly be notified and orchestrate their efforts to promptly respond to the requests.PHDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/166144/1/yanchenm_1.pd

Sliding mode control for a surgical teleoperation system via a disturbance observer

To obtain accurate trajectory tracking with robustness and faithful force feedback in a practical application, a sliding mode controller (SMC) combined with a compensation controller based on a nonlinear disturbance observer (DOB) is proposed. The DOB estimates the disturbances arising mainly from the uncertain dynamic model of a surgical manipulator, frictional forces and external interaction forces, and compensates for these disturbances in the control law. Accordingly, it alleviates the chattering problem caused by t

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 12th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2020, held in Leiden, The Netherlands, in September 2020. The 60 papers presented in this volume were carefully reviewed and selected from 111 submissions. The were organized in topical sections on haptic science, haptic technology, and haptic applications. This year's focus is on accessibility

Human-Robot Collaborations in Industrial Automation

Technology is changing the manufacturing world. For example, sensors are being used to track inventories from the manufacturing floor up to a retail shelf or a customer’s door. These types of interconnected systems have been called the fourth industrial revolution, also known as Industry 4.0, and are projected to lower manufacturing costs. As industry moves toward these integrated technologies and lower costs, engineers will need to connect these systems via the Internet of Things (IoT). These engineers will also need to design how these connected systems interact with humans. The focus of this Special Issue is the smart sensors used in these human–robot collaborations

Multi-Platform Intelligent System for Multimodal Human-Computer Interaction

We present a flexible human--robot interaction architecture that incorporates emotions and moods to provide a natural experience for humans. To determine the emotional state of the user, information representing eye gaze and facial expression is combined with other contextual information such as whether the user is asking questions or has been quiet for some time. Subsequently, an appropriate robot behaviour is selected from a multi-path scenario. This architecture can be easily adapted to interactions with non-embodied robots such as avatars on a mobile device or a PC. We present the outcome of evaluating an implementation of our proposed architecture as a whole, and also of its modules for detecting emotions and questions. Results are promising and provide a basis for further development