Collaborative Control for a Robotic Wheelchair: Evaluation of Performance, Attention, and Workload

Powered wheelchair users often struggle to drive safely and effectively and in more critical cases can only get around when accompanied by an assistant. To address these issues, we propose a collaborative control mechanism that assists the user as and when they require help. The system uses a multiple–hypotheses method to predict the driver’s intentions and if necessary, adjusts the control signals to achieve the desired goal safely. The main emphasis of this paper is on a comprehensive evaluation, where we not only look at the system performance, but, perhaps more importantly, we characterise the user performance, in an experiment that combines eye–tracking with a secondary task. Without assistance, participants experienced multiple collisions whilst driving around the predefined route. Conversely, when they were assisted by the collaborative controller, not only did they drive more safely, but they were able to pay less attention to their driving, resulting in a reduced cognitive workload. We discuss the importance of these results and their implications for other applications of shared control, such as brain–machine interfaces, where it could be used to compensate for both the low frequency and the low resolution of the user input

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

Learning-Based Adaptation for Personalized Mobility Assistance

Mobility assistance is of key importance for people with disabilities to remain autonomous in their preferred environments. In severe cases, assistance can be provided by robotized wheelchairs that can perform complex maneuvers and/or correct the user’s commands. User’s acceptance is of key importance, as some users do not like their commands to be modified. This work presents a solution to improve acceptance. It consists of making the robot learn how the user drives so corrections will not be so noticeable to the user. Case Based Reasoning (CBR) is used to acquire a user’s driving model reactive level. Experiments with volunteers at Fondazione Santa Lucia (FSL) have proven that, indeed, this customized approach at assistance increases acceptance by the user.This work has been partially supported by the Spanish Ministerio de Educacion y Ciencia (MEC), Project TEC2011-29106-C02-01. The authors would like to thank Santa Lucia Hospedale and all volunteers for their kind cooperation and Sauer Medica for providing the power wheelchair

A Low-Cost Tele-Presence Wheelchair System

This paper presents the architecture and implementation of a tele-presence wheelchair system based on tele-presence robot, intelligent wheelchair, and touch screen technologies. The tele-presence wheelchair system consists of a commercial electric wheelchair, an add-on tele-presence interaction module, and a touchable live video image based user interface (called TIUI). The tele-presence interaction module is used to provide video-chatting for an elderly or disabled person with the family members or caregivers, and also captures the live video of an environment for tele-operation and semi-autonomous navigation. The user interface developed in our lab allows an operator to access the system anywhere and directly touch the live video image of the wheelchair to push it as if he/she did it in the presence. This paper also discusses the evaluation of the user experience

Co-construction of chronic illness narratives by older stroke survivors and their spouses

Illness narratives have mainly focused on individual patients' accounts, and particularly those of people experiencing the onset of chronic illness in mid-life. However, a growing number of older people are spending their later life with their partner, with both experiencing complex morbidities. We examine the shared creation of meanings among older stroke survivors and their spouses and the implications for individual and couple identity. Joint biographical narrative interviews were held with 13 stroke survivors aged 75-85 and their spouses. The analysis examined both narrative content and narrative style. Three main types of co-presentation of identity were identified. The 'united couple' described couples who pulled together and emphasised their accommodation of the stroke and normality as a couple, despite often considerable disability, and was strongly underpinned by collaborative interaction in interviews. Caring relationships were distinguished as 'positive', involving self-reliant couples who took pride in how they managed and 'frustrated' in couples who emphasised the difficulties of caring and hardships experienced and were characterised by a conflictual style of narrative. We argue that joint interviews provide new forms of data that extend notions of how illness is lived and demonstrates how the marital relationship can mediate the experience of chronic illness and disability and its impact on identity. © 2013 The Authors. Sociology of Health & Illness © 2013 Foundation for the Sociology of Health & Illness/JohnWiley & Sons Ltd

Preparing teachers to support inclusion: The benefits of interaction between a group of pre-service teachers and a teaching assistant who is disabled.

This qualitative study investigates the development of preservice teachers' attitudes toward people with disabilities during a semester-long unit. Ten students enrolled in a special education teaching elective were interviewed before and after they were engaged in a teaching program designed to expose them to direct, structured interactions with a teaching assistant who was physically disabled. The teaching assistant interacted with students in both small and large group tutorial discussions throughout the semester. Also, students kept a reflective journal on their experiences with people with disabilities throughout the teaching program. Data were collected through the use of semi-structured interviews and journals, and analysis indicated that: (i) students developed a more positive attitude and became more comfortable in interacting with the teaching assistant during the semester, and (ii) learning experience improved their knowledge about disability issues

Learning shared control by demonstration for personalized wheelchair assistance

An emerging research problem in assistive robotics is the design of methodologies that allow robots to provide personalized assistance to users. For this purpose, we present a method to learn shared control policies from demonstrations offered by a human assistant. We train a Gaussian process (GP) regression model to continuously regulate the level of assistance between the user and the robot, given the user's previous and current actions and the state of the environment. The assistance policy is learned after only a single human demonstration, i.e. in one-shot. Our technique is evaluated in a one-of-a-kind experimental study, where the machine-learned shared control policy is compared to human assistance. Our analyses show that our technique is successful in emulating human shared control, by matching the location and amount of offered assistance on different trajectories. We observed that the effort requirement of the users were comparable between human-robot and human-human settings. Under the learned policy, the jerkiness of the user's joystick movements dropped significantly, despite a significant increase in the jerkiness of the robot assistant's commands. In terms of performance, even though the robotic assistance increased task completion time, the average distance to obstacles stayed in similar ranges to human assistance