Spatial context-aware person-following for a domestic robot

Domestic robots are in the focus of research in terms of service providers in households and even as robotic companion that share the living space with humans. A major capability of mobile domestic robots that is joint exploration of space. One challenge to deal with this task is how could we let the robots move in space in reasonable, socially acceptable ways so that it will support interaction and communication as a part of the joint exploration. As a step towards this challenge, we have developed a context-aware following behav- ior considering these social aspects and applied these together with a multi-modal person-tracking method to switch between three basic following approaches, namely direction-following, path-following and parallel-following. These are derived from the observation of human-human following schemes and are activated depending on the current spatial context (e.g. free space) and the relative position of the interacting human. A combination of the elementary behaviors is performed in real time with our mobile robot in different environments. First experimental results are provided to demonstrate the practicability of the proposed approach

Identification of Haptic Based Guiding Using Hard Reins

This paper presents identifications of human-human interaction in which one person with limited auditory and visual perception of the environment (a follower) is guided by an agent with full perceptual capabilities (a guider) via a hard rein along a given path. We investigate several identifications of the interaction between the guider and the follower such as computational models that map states of the follower to actions of the guider and the computational basis of the guider to modulate the force on the rein in response to the trust level of the follower. Based on experimental identification systems on human demonstrations show that the guider and the follower experience learning for an optimal stable state-dependent novel 3rd and 2nd order auto-regressive predictive and reactive control policies respectively. By modeling the follower's dynamics using a time varying virtual damped inertial system, we found that the coefficient of virtual damping is most appropriate to explain the trust level of the follower at any given time. Moreover, we present the stability of the extracted guiding policy when it was implemented on a planar 1-DoF robotic arm. Our findings provide a theoretical basis to design advanced human-robot interaction algorithms applicable to a variety of situations where a human requires the assistance of a robot to perceive the environment

Quoi de neuf en asservissement visuel depuis les JNRR'03 ?

National audienceCet article de synthèse présente les avancées réalisées en France au cours de ces quatre dernières années dans le domaine de l'asservissement visuel

Salient Feature of Haptic-Based Guidance of People in Low Visibility Environments Using Hard Reins

This paper presents salient features of human–human interaction where one person with limited auditory and visual perception of the environment (a follower) is guided by an agent with full perceptual capabilities (a guider) via a hard rein along a given path. We investigate several salient features of the interaction between the guider and follower such as: 1) the order of an autoregressive (AR) control policy that maps states of the follower to actions of the guider; 2) how the guider may modulate the pulling force in response to the trust level of the follower; and 3) how learning may successively apportion the responsibility of control across different muscles of the guider. Based on experimental systems identification on human demonstrations from ten pairs of naive subjects, we show that guiders tend to adopt a third-order AR predictive control policy and followers tend to adopt second-order reactive control policy. Moreover, the extracted guider’s control policy was implemented and validated by human–robot interaction experiments. By modeling the follower’s dynamics with a time varying virtual damped inertial system, we found that it is the coefficient of virtual damping which is most sensitive to the trust level of the follower. We used these experimental insights to derive a novel controller that integrates an optimal order control policy with a push/pull force modulator in response to the trust level of the follower monitored using a time varying virtual damped inertial model

Longitudinal control for person-following robots

Purpose: This paper aims to address the longitudinal control problem for person-following robots (PFRs) for the implementation of this technology. Design/methodology/approach: Nine representative car-following models are analyzed from PFRs application and the linear model and optimal velocity model/full velocity difference model are qualified and selected in the PFR control. Findings: A lab PFR with the bar-laser-perception device is developed and tested in the field, and the results indicate that the proposed models perform well in normal person-following scenarios. Originality/value: This study fills a gap in the research on PRFs longitudinal control and provides a useful and practical reference on PFRs longitudinal control for the related research

물체 수송을 위한 협업 로봇의 행동 연구

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 2. 이범희.This dissertation presents two cooperative object transportation techniques according to the characteristics of objects: passive and active. The passive object is a typical object, which cannot communicate with and detect other robots. The active object, however, has abilities to communicate with robots and can measure the distance from other robots using proximity sensors. Typical areas of research in cooperative object transportation include grasping, pushing, and caging techniques, but these require precise grasping behaviors, iterative motion correction according to the object pose, and the real-time acquisition of the object shape, respectively. For solving these problems, we propose two new object transportation techniques by considering the properties of objects. First, this dissertation presents a multi-agent behavior to cooperatively transport an active object using a sound signal and interactive communication. We first developed a sound localization method, which estimates the sound source from an active object by using three microphone sensors. Next, since the active object cannot be recalled by only a single robot, the robots organized a heterogeneous team by themselves with a pusher, a puller, and a supervisor. This self-organized team succeeded in moving the active object to a goal using the cooperation of its neighboring robots and interactive communication between the object and robots. Second, this dissertation presents a new cooperative passive object transportation technique using cyclic shift motion. The proposed technique does not need to consider the shape or the pose of objects, and equipped tools are also unnecessary for object transportation. Multiple robots create a parallel row formation using a virtual electric dipole field and then push multiple objects into the formation. This parallel row is extended to the goal using cyclic motion by the robots. The above processes are decentralized and activated based on the finite state machine of each robot. Simulations and practical experiments are presented to verify the proposed techniques.Chapter 1 Introduction 1 1.1 Background and Motivation 1 1.2 Related Work 4 1.2.1 The Categories of Object Transportation Techniques 4 1.2.2 Sound Localization Techniques for Active Object Transportation 7 1.3 Contributions 8 1.4 Organization 10 Chapter 2 Object Transportation Problem 11 2.1 Passive Object versus Active Object 11 2.2 Problem Formulation 13 2.3 Assumptions 13 Chapter 3 Active Object Transportation using a Sound Signal and Interactive Communication 15 3.1 Overview of Active Object Transportation 16 3.2 Sound Vector Generation using Triple Microphones 17 3.2.1 Sound Isocontour Generation using ILD 18 3.2.2 Sound Circle Generation using Inverse-square Law 21 3.2.3 Sound Vector Generation 22 3.3 Cooperative Control Method using Interactive Communication 25 3.3.1 Role Assignment of Multi-robot Team 25 3.3.2 Position Assignment of Multi-robot Team 26 3.3.3 Transportation Process of an Active Object 29 Chapter 4 Passive Object Transportation using Cyclic Shift Motion 33 4.1 Overview of Passive Object Transportation 34 4.2 Multi-robot Team Organization 35 4.3 Row Formation Generation using Multiple Robots 37 4.3.1 Cyclic Shift Motion 37 4.3.2 Path Generation using Virtual Electric Dipole Field 39 4.3.3 Path Following using Bang-bang Controller 42 4.4 Multi-object Transportation by a Decentralized Multi-robot Team 45 4.4.1 Information Acquisition Methods for Finite State Machine 45 4.4.2 Finite State Machines (FSMs) 48 4.4.2.1 The FSM of Guider Robots 49 4.4.2.2 The FSM of a Pusher Robot 52 4.4.2.3 The FSM of a Leader Robot 54 4.4.3 Object Transportation Process 55 4.4.4 Formation Constraints for Curved Transportation Path 57 Chapter 5 Simulation Results 61 5.1 Simulation Environment 61 5.2 Simulation Result of Passive Object Transportation 63 5.3 Comparison Results with Other Passive Object Transportation Techniques 69 5.3.1 Simulation Result of Leader-Follower Technique 70 5.3.2 Simulation Result of Caging Technique 72 Chapter 6 Practical Experiments 77 6.1 Experimental Environment 77 6.2 Experimental Results of Active Object Transportation 81 6.2.1 Experimental Result of the SV Estimation 81 6.2.2 Experimental Result of Active Object Transportation 82 6.3 Experimental Results of Passive Object Transportation 86 6.3.1 Small-object Transportation with Straight Path 86 6.3.2 Small-object Transportation with Curved Path 91 6.3.3 Large-object Transportation 93 6.4 Comparison Result with Caging Technique 95 Chapter 7 Discussion 96 Chapter 8 Conclusions 99 Appendix A: The Approaching Phase of Passive Object Transportation 101 A.1 Approaching Phase 101 A.2 Experimental Result of Approaching Phase 107 Appendix B: Object Transportation in a Static Environment 109 B.1 Overview 109 B.2 Object Transportation Problem in a Static Environment 111 B.3 Multi-object Transportation using Hybrid System 112 B.4 New Finite State Machines 113 B.4.1 The States of Guider Robots 114 B.4.2 The States of a Pusher Robot 115 B.4.3 The States of a Leader Robot 116 B.5 Simulation Results 118 B.5.1 Simulation Result: An Obstacle 118 B.5.2 Simulation Result: Two Obstacles 120 B.6 Practical Experiment 122 Bibliography 124Docto

Mobile assistive technologies for the visually impaired

There are around 285 million visually impaired people worldwide, and around 370,000 people are registered as blind or partially sighted in the UK. Ongoing advances in information technology (IT) are increasing the scope for IT-based mobile assistive technologies to facilitate the independence, safety, and improved quality of life of the visually impaired. Research is being directed at making mobile phones and other handheld devices accessible via our haptic (touch) and audio sensory channels. We review research and innovation within the field of mobile assistive technology for the visually impaired and, in so doing, highlight the need for successful collaboration between clinical expertise, computer science, and domain users to realize fully the potential benefits of such technologies. We initially reflect on research that has been conducted to make mobile phones more accessible to people with vision loss. We then discuss innovative assistive applications designed for the visually impaired that are either delivered via mainstream devices and can be used while in motion (e.g., mobile phones) or are embedded within an environment that may be in motion (e.g., public transport) or within which the user may be in motion (e.g., smart homes)

Human aware robot navigation

Abstract. Human aware robot navigation refers to the navigation of a robot in an environment shared with humans in such a way that the humans should feel comfortable, and natural with the presence of the robot. On top of that, the robot navigation should comply with the social norms of the environment. The robot can interact with humans in the environment, such as avoiding them, approaching them, or following them. In this thesis, we specifically focus on the approach behavior of the robot, keeping the other use cases still in mind. Studying and analyzing how humans move around other humans gives us the idea about the kind of navigation behaviors that we expect the robots to exhibit. Most of the previous research does not focus much on understanding such behavioral aspects while approaching people. On top of that, a straightforward mathematical modeling of complex human behaviors is very difficult. So, in this thesis, we proposed an Inverse Reinforcement Learning (IRL) framework based on Guided Cost Learning (GCL) to learn these behaviors from demonstration. After analyzing the CongreG8 dataset, we found that the incoming human tends to make an O-space (circle) with the rest of the group. Also, the approaching velocity slows down when the approaching human gets closer to the group. We utilized these findings in our framework that can learn the optimal reward and policy from the example demonstrations and imitate similar human motion

A model for assessment of human assistive robot capability

The purpose of this research is to develop a generalised model for levels of autonomy and sophistication for autonomous systems. It begins with an introduction to the research, its aims and objectives before a detailed review of related literature is presented as it pertains to the subject matter and the methodology used in the research. The research tasks are carried out using appropriate methods including literature reviews, case studies and semi-structured interviews. Through identifying the gaps in the current work on human assistive robots, a generalised model for assessing levels of autonomy and sophistication for human assistive robots (ALFHAR) is created through logical modelling, semi-structured interview methods and case studies. A web-based tool for the ALFHAR model is also created to support the model application. The ALFHAR model evaluates levels of autonomy and sophistication with regard to the decision making, interaction, and mechanical ability aspects of human assistive robots. The verification of the model is achieved by analysing evaluation results from the web-based tool and ALFHAR model. The model is validated using a set of tests with stakeholders participation through the conduction of a case study using the web-based tool. The main finding from this research is that the ALFHAR model can be considered as a model to be used in the evaluation of levels of autonomy and sophistication for human assistive robots. It can also prove helpful as part of through life management support for autonomous systems. The thesis concludes with a critical review of the research and some recommendations for further research