Influences on proxemic behaviors in human-robot interaction

Abstract — As robots enter the everyday physical world of people, it is important that they abide by society’s unspoken social rules such as respecting people’s personal spaces. In this paper, we explore issues related to human personal space around robots, beginning with a review of the existing literature in human-robot interaction regarding the dimensions of people, robots, and contexts that influence human-robot interactions. We then present several research hypotheses which we tested in a controlled experiment (N=30). Using a 2 (robotics experi-ence vs. none: between-participants) x 2 (robot head oriented toward a participant’s face vs. legs: within-participants) mixed design experiment, we explored the factors that influence proxemic behavior around robots in several situations: (1) people approaching a robot, (2) people being approached by an autonomously moving robot, and (3) people being approached by a teleoperated robot. We found that personal experience with pets and robots decreases a person’s personal space around robots. In addition, when the robot’s head is oriented toward the person’s face, it increases the minimum comfortable distance for women, but decreases the minimum comfortable distance for men. We also found that the personality trait of agreeableness decreases personal spaces when people approach robots, while the personality trait of neuroticism and having negative attitudes toward robots increase personal spaces when robots approach people. These results have implications for both human-robot interaction theory and design. I

Pose Embeddings: A Deep Architecture for Learning to Match Human Poses

We present a method for learning an embedding that places images of humans in similar poses nearby. This embedding can be used as a direct method of comparing images based on human pose, avoiding potential challenges of estimating body joint positions. Pose embedding learning is formulated under a triplet-based distance criterion. A deep architecture is used to allow learning of a representation capable of making distinctions between different poses. Experiments on human pose matching and retrieval from video data demonstrate the potential of the method

AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions

This paper introduces a video dataset of spatio-temporally localized Atomic Visual Actions (AVA). The AVA dataset densely annotates 80 atomic visual actions in 430 15-minute video clips, where actions are localized in space and time, resulting in 1.58M action labels with multiple labels per person occurring frequently. The key characteristics of our dataset are: (1) the definition of atomic visual actions, rather than composite actions; (2) precise spatio-temporal annotations with possibly multiple annotations for each person; (3) exhaustive annotation of these atomic actions over 15-minute video clips; (4) people temporally linked across consecutive segments; and (5) using movies to gather a varied set of action representations. This departs from existing datasets for spatio-temporal action recognition, which typically provide sparse annotations for composite actions in short video clips. We will release the dataset publicly. AVA, with its realistic scene and action complexity, exposes the intrinsic difficulty of action recognition. To benchmark this, we present a novel approach for action localization that builds upon the current state-of-the-art methods, and demonstrates better performance on JHMDB and UCF101-24 categories. While setting a new state of the art on existing datasets, the overall results on AVA are low at 15.6% mAP, underscoring the need for developing new approaches for video understanding.Comment: To appear in CVPR 2018. Check dataset page https://research.google.com/ava/ for detail

Help me help you: Interfaces for personal robots

Index Terms—HRI, mobile user interface, information theor

Help me help you: Interfaces for personal robots

Index Terms-HRI, mobile user interface, information theory I. RESEARCH PROBLEM AND A PROPOSAL The communication bottleneck between robots and people People are adept at compensating for communication limitations, changing their communicative strategies for talking to pets, babies We propose to approach this problem by accounting for limitations in robot abilities and taking advantage of already familiar human-computer interaction models, leveraging a communication model based upon Information Theory. Using this design perspective, we present three different mobile user interfaces that were fully developed and implemented on a PR2 (Personal Robot 2) [6] for task domains in navigation, perception, learning and manipulation. II. RELEVANT THEORIES We can observe parallels between human robot interaction and the interaction between humans and general complex autonomous systems. Sheridan's taxonomy of complex human-machine systems describes the following sequence of operations: (1) acquire information, (2) analyze and display information, (3) decide on an action, and (4) implement that action [7, p. 61]. This provides the groundwork for identifying the stages at which people and/or robots should lead. In the current projects, the personal robot autonomously completes steps 1, 2 and 4, and the person completes step 3. Thus, the user interface design must address how the robot analyzes and displays its sensor information and world model to the human, and how the human can effectively communicate desired actions to the robot. An analysis of our case studies in Sheridan's framework is displayed in Gold proposed using an Information Pipeline model for HRI that is based upon information theory [8], a mathematical model of communication developed for quantifying the amount of information that could be transported through a given channel. Schramm [9] developed a theory of communication that put these ideas into the context of two-way joint communications. This could be helpful when considering the large amount of overhead involved in encoding and decoding messages sent between people and robots. The focus of the projects in this paper was on designing interfaces that applied this theory to human-robot communication. With a robot encoding messages in a way that humans can understand and humans encoding messages in a way that robots can understand, communication is easy and effective. III. THE DESIGN SPACE AND THREE UIS The personal robot platform used throughout these projects is the PR2, and the robot behaviors are built using the Robot Operating System (ROS

Robots for Humanity: Using Assistive Robots to Empower People with Disabilities

Assistive mobile manipulators have the potential to one day serve as surrogates and helpers for people with disabilities, giving them the freedom to perform tasks such as scratching an itch, picking up a cup, or socializing with their families. This article introduces a collaborative project with the goal of putting assistive mobile manipulators into real homes to work with people with disabilities. Through a participatory design process in which users have been actively involved from day one, we are identifying and developing assistive capabilities for the PR2 robot. Our approach is to develop a diverse suite of open source software tools that blend the capabilities of the user and the robot. Within this article, we introduce the project, describe our progress, and discuss lessons we have learned.This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by IEEE-Institute of Electrical and Electronics Engineers and can be found at: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=100. ©2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Keywords: Medical robotics, Biomedical equipment, Robots, Control systems, Handicapped aids, Software development, Exoskeletons, Sensory aids, Human factors, Prosthetic