ATTITUDE AWARE SMARTPHONES FOR TELE-OPERATED ROBOT CONTROL

The U.S. military has increasingly turned to unmanned ground vehicles (UGVs) to assist in the most dull, dirty, and dangerous missions. Their presence on the battlefield is redefining how war is waged, expanding opportunities for reconnaissance and surveillance while minimizing soldier mortality. Robotic systems have gotten ever smaller, many now being man-packable. Soldiers may now carry, deploy, and control their own robotic assistant, many with limited formal training. Unfortunately, UGVs add significantly to a soldier's standard load of water, ammunition, armor, and supplies, making weight and portability top concerns. One way to ease the soldier burden is to adopt smartphones for use as robot operator control units (OCUs). Their small, lightweight frame combined with processing power and adaptable software backbone may enable intuitive controls on a device well-suited for other military missions.Field operations are often conducted when users are gloved and/or dirty, making common smartphone touch interfaces problematic. By using proprioceptive device inputs related to attitude, smartphones can be used for control in ways that minimize that touch interface. To test this, an attitude aware smartphone controller (using the device's accelerometers and gyroscope) for a small, tele-operated, ground robot was developed and assessed via a multi-phase usability experiment. The controller's motion algorithm made use of quaternion mathematics to simplify motion handling and the user interface.Twenty-five users were recruited to assess usability of attitude aware controls, testing their suitability for driving and camera manipulation tasks. Participants operated a small tracked robot on an indoor course with controllers using either virtual joystick or tilt-based controls while metrics regarding performance, mental workload, and user satisfaction were collected. They were also exposed to customizable controls, identifying modes and settings which contributed most heavily to the controller's usability. Results indicate that attitude-based controls are suitable for tele-operated reconnaissance and surveillance, as 64% of users preferred tilt-based driving controls while performing equally as well as the alternative. Customized configurations showed 60% of users preferred tilt for driving tasks when throttle sensitivity and controller responsiveness could be manipulated. The inherent usability of attitude aware controls optimistically exhibit how smartphones can be leveraged for robotic control, even in harsh environments by gloved users

3D smart user interactive system with real-time responding tele-robotic proprioceptive information

Feedback of proprioceptive information is essential for many tele-robotic systems, especially those designed to undertake tasks concerning hazardous environments and for efficient out-of-sight remote control applications. Given highly sensitive nature of these applications, even small errors (e.g. less than one degree of displacement in robot posture) can cause unnecessary risk. Thus, accurate feedback of proprioceptive information, as well as a technique to precisely interpret this information, is significant to operator. In this paper, we introduce a framework that uses pulse feedback mechanism to measure the proprioceptive information of a robot operating over real-time wireless communication and represent it in 3D model user interface. The 3D user interface enhances the interpretation of proprioceptive information to help operator to visualize the real-time relative position of the robot. The paper also provides results that demonstrate how the framework allows synchronization between 3D model and tele-robot to be achieved in real-time over wireless communications

Spatial Orientation Aware Smartphones for Tele-operated Robot Control in Military Environments: A Usability Experiment

We report an experiment conducted to assess the usability of a smartphone-based controller for use by dismounted troops using unmanned ground vehicles for reconnaissance and surveillance. A virtual joystick controller is compared to a specially designed tilt-based controller intended to limit the device’s touch interface while providing intuitive control. Participants drove a small tracked robot on an indoor course using both controller options where metrics regarding performance, mental workload, and user satisfaction represented various measures of controller usability. Results indicate that the tilt controller is preferred by users and performs equally as well, if not better, on most performance metrics. These results support the development of a smartphone-based control option for military robotics, with a focus on gestural input methods which overcome deficiencies of current touch-based systems, namely lack of physical feedback, high attention demands, and unreliability in field environments.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

A fast and robust deep convolutional neural networks for complex human activity recognition using smartphone

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. As a significant role in healthcare and sports applications, human activity recognition (HAR) techniques are capable of monitoring humans’ daily behavior. It has spurred the demand for intelligent sensors and has been giving rise to the explosive growth of wearable and mobile devices. They provide the most availability of human activity data (big data). Powerful algorithms are required to analyze these heterogeneous and high-dimension streaming data efficiently. This paper proposes a novel fast and robust deep convolutional neural network structure (FR-DCNN) for human activity recognition (HAR) using a smartphone. It enhances the effectiveness and extends the information of the collected raw data from the inertial measurement unit (IMU) sensors by integrating a series of signal processing algorithms and a signal selection module. It enables a fast computational method for building the DCNN classifier by adding a data compression module. Experimental results on the sampled 12 complex activities dataset show that the proposed FR-DCNN model is the best method for fast computation and high accuracy recognition. The FR-DCNN model only needs 0.0029 s to predict activity in an online way with 95.27% accuracy. Meanwhile, it only takes 88 s (average) to establish the DCNN classifier on the compressed dataset with less precision loss 94.18%

Real-time sensor data integration in vertical transport systems

In this project, mobile connectivity and an innovative approach to sensor data gathering and integration have been employed to automate maintenance inspection, performance monitoring and ride quality measurement in vertical transportation systems. An Inertial Navigation System (INS) has been proposed, implemented and tested to track lift car movement profile. The inherent characteristics of vertical motion have been used to minimize errors and obtain higher accuracy in the integration results. The measurement of a correlation between kinematic profiles constructed from lift-car tracking data compared to its nominal values provides key information on the lift condition at any time. A frequency analysis was applied to processing vibrations and noise data, effectively adding another dimension to the lift ride quality measurement. This approach enabled lift performance profiles to be compiled automatically and transmitted in real time, which significantly rationalized and improved the process of maintenance inspection and monitoring. An advanced prototype, AdInspect, has been produced, with the full set of described features. Industry partners are currently evaluating it

Exploring Children’s Beliefs for Adoption or Rejection of Domestic Social Robots

With social robots entering the consumer market, there is a growing need to study child-robot interaction in a domestic environment. Therefore, the aim of this study was to explore children’s beliefs that underlie their intended adoption or rejection of a social robot for use in their homes. Based on a content analysis of data from 87 children, we found that hedonic beliefs (i.e., the belief that having a robot at home is pleasurable) were the most mentioned beliefs for domestic adoption of a social robot. More specifically, companionship was an often-mentioned hedonic belief. Social beliefs were rarely mentioned. If children mentioned beliefs for rejecting the robot, they often referred to family members and family composition. The findings of this exploratory study thus suggest that children’s hedonic beliefs play a central role in their intended adoption of a social robot in a domestic environment

On the use of haptic tablets for UGV teleoperation in unstructured environments: system design and evaluation

Teleoperation of Unmanned Ground Vehicles (UGVs), particularly for inspection of unstructured and unfamiliar environments still raises important challenges from the point of view of the operator interface. One of these challenges is caused by the fact that all information available to the operator is presented to the operator through a computer interface, providing only a partial view of the robot situation. The majority of existing interfaces provide information using visual, and, less frequently, sound channels. The lack of Situation Awareness (SA), caused by this partial view, may lead to an incorrect and inefficient response to the current UGV state, usually confusing and frustrating the human operator. For instance, the UGV may become stuck in debris while the operator struggles to move the robot, not understanding the cause of the UGV lack of motion. We address this problem by studying the use of haptic feedback to improve operator SA. More precisely, improving SA with respect to the traction state of the UGV, using a haptic tablet for both commanding the robot and conveying traction state to the user by haptic feedback. We report (1) a teleoperating interface, integrating a haptic tablet with an existing UGV teleoperation interface, and (2) the experimental results of a user study designed to evaluate the advantage of this interface in the teleoperation of a UGV, in a search and rescue scenario. Statistically significant results were found supporting the hypothesis that using the haptic tablet elicits a reduction in the time that the UGV spends in states without traction.info:eu-repo/semantics/publishedVersio

5G Smart and innovative Healthcare services: opportunities, challenges and prospective solutions

Due to its abilities to boost productivity, reduce costs and enhance user experiences, smart healthcare is widely recognised as a potential solution to reduce pressures on existing health systems. Since the new era of 5G will unite enhanced connectivity, improved cloud-based storage and interconnection of an array of devices and services, a massive boost in the digital transformation of healthcare is expected. In this transformation process, healthcare services such as medical diagnosis, treatment and remote surgery will be facilitated by a range of technologies such as Internet of Things, Robotics and Artificial Intelligence, among others, that will advance further under 5G. Moreover, real-time health services will become a reality and will offer people with quality care and improved experiences. On the other hand, different challenges can hinder the proliferation of 5G smart and innovative healthcare solutions, including security and heterogeneous devices. This chapter presents how 5G will boost digital transformation of healthcare through delivery and consumption of smart and innovative healthcare services, while probing into key hurdles in the process as well as prospective solutions

Human-Like Guide Robot that Proactively Explains Exhibits

We developed an autonomous human-like guide robot for a science museum. Its identifies individuals, estimates the exhibits at which visitors are looking, and proactively approaches them to provide explanations with gaze autonomously, using our new approach called speak-and-retreat interaction. The robot also performs such relation-building behaviors as greeting visitors by their names and expressing a friendlier attitude to repeat visitors. We conducted a field study in a science museum at which our system basically operated autonomously and the visitors responded quite positively. First-time visitors on average interacted with the robot for about 9 min, and 94.74% expressed a desire to interact with it again in the future. Repeat visitors noticed its relation-building capability and perceived a closer relationship with it