Robot-enabled support of daily activities in smart home environments

Wilson, Garrett; Pereyda, Christopher; Raghunath, Nisha; Cruz, Gabriel; Goel, Shivam; Nesaei, Sepehr; Minor, Bryan; Schmitter‐Edgecombe, Maureen; Taylor, Matthew E.; Cook, Diane J.

doi:10.1016/j.cogsys.2018.10.032

Cited by 87 publications

(46 citation statements)

References 47 publications

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“…Other solutions consider the possibility of integrating a robot platform into a smart home environment such that its functionalities may be augmented. An example is the robot activity support system (RAS) created by Washington State University [34] for adults with memory problems and other impairments to help them to live independently. Thus, the smart home has sensors in the walls to track the user's movement and feeds their data into the robot's neural network.…”

Section: Older Adult Carementioning

confidence: 99%

Socially Assistive Robots for Older Adults and People with Autism: An Overview

2020

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Over one billion people in the world suffer from some form of disability. Nevertheless, according to the World Health Organization, people with disabilities are particularly vulnerable to deficiencies in services, such as health care, rehabilitation, support, and assistance. In this sense, recent technological developments can mitigate these deficiencies, offering less-expensive assistive systems to meet users’ needs. This paper reviews and summarizes the research efforts toward the development of these kinds of systems, focusing on two social groups: older adults and children with autism.

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Section: Older Adult Carementioning

confidence: 99%

Socially Assistive Robots for Older Adults and People with Autism: An Overview

2020

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“…Robots with LiDAR systems have been proposed for remote surveillance of hazardous areas leveraging Simultaneous Localization and Mapping (SLAM) [5]. Robots with LiDAR systems are also used in smart environments as activity monitoring and health assessment [6].…”

Section: Related Workmentioning

confidence: 99%

Auto-Encoding Robot State Against Sensor Spoofing Attacks

Rivera

Lagraa

Iannillo

et al. 2019

2019 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)

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In robotic systems, the physical world is highly coupled with cyberspace. New threats affect cyber-physical systems as they rely on several sensors to perform critical operations. The most sensitive targets are their location systems, where spoofing attacks can force robots to behave incorrectly. In this paper, we propose a novel anomaly detection approach for sensor spoofing attacks, based on an auto-encoder architecture. After initial training, the detection algorithm works directly on the compressed data by computing the reconstruction errors. We focus on spoofing attacks on Light Detection and Ranging (LiDAR) systems. We tested our anomaly detection approach against several types of spoofing attacks comparing four different compression rates for the auto-encoder. Our approach has a 99% True Positive rate and a 10% False Negative rate for the 83% compression rate. However, a compression rate of 41% could handle almost all of the same attacks while using half the data.

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“…Wilson et al [22] discuss how smart environments offer valuable technologies for activity monitoring and health assessment with a specific reference to integration of robots into smart environments in order to provide more interactive support of individuals with functional limitations. They describe their system RAS (Robot Activity Support) system which partners smart environment sensing, object detection and mapping,and robot interaction to detect and assist with activity errors that may occur in everyday settings.…”

Section: Summary Of the Special Issuementioning

confidence: 99%