Anticipative Shared Control for Robotic Wheelchairs Used by People with Disabilities

Pinheiro, Paulo Gurgel; Cardozo, Eleri; Pinheiro, Claudio Gurgel

doi:10.1109/icarsc.2015.26

Cited by 10 publications

(4 citation statements)

References 11 publications

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“…Improving human models provides better information that can inform how and/or when to provide robot assistance (Pentland & Liu, ). Prior work in this area has considered robot teleoperation scenarios (Dragan, Lee, & Srinivasa, ), cooperative motion planning (Hauser, ), and assistive technology (Demeester et al, ; Pinheiro, Cardozo, & Pinheiro, ). In our work, rather than continuously predicting the user’s actions, we use the prediction of their skill level to make a generalization of what actions the user will most likely perform.…”

Section: Research Applicationsmentioning

confidence: 99%

Shared autonomy for low‐cost underwater vehicles

Lawrance

DeBortoli

Jones

et al. 2018

Journal of Field Robotics

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This field report presents an overview of the development and testing of a semiautonomous underwater vehicle (sAUV). The work presented here is aimed at bridging the gap between current remotely operated vehicles and autonomous research platforms by developing shared autonomy capabilities for low-cost underwater vehicles. We use commercially available components and open-source software interfaces to provide a wider range of capabilities for underwater autonomy research at a lower cost than previously available systems. We describe the overall structure of the system, discuss its capabilities, and provide results demonstrating system performance. We place particular emphasis on shared autonomy, where a human operator is assisted in controlling an underwater tethered vehicle. We present three capabilities developed for the sAUV: (a) an assisted control mode that provides a variable level of assistance using an on-line estimate of user skill level, (b) a planner to generate paths that avoid tether entanglement, and (c) a sonar processing algorithm that identifies informative sonar images for selecting features for 3D scene reconstruction. The vehicle has been deployed on five off-shore and near-shore marine field deployments since 2015, and this report includes selected results from four of those trials to demonstrate the capabilities and limitations of the sAUV system. K E Y W O R D S human robot interaction, perception, planning, underwater robotics 1 | INTRODUCTION Unmanned underwater vehicles (UUVs) are used for a wide variety of tasks, from short-duration (hour-scale) inspection tasks to longduration (month-scale) data gathering missions. Within this group of vehicles there exists a wide range of autonomous capability, from limited or no autonomy on most industry-standard remotely operated vehicles (ROVs) to full autonomy on research-grade autonomous underwater vehicles (AUVs). In this paper, we examine partial-autonomy approaches that leverage the capabilities of autonomous systems to complement the skills of human operators.We use the term semi-autonomous to refer to a system that has some autonomous capabilities but must rely on a human operator for certain mission-critical capabilities. In this study, we develop and demonstrate a semi-autonomous underwater vehicle (sAUV) system.One of the primary limitations to deployment of AUVs is the perception that autonomy capabilities are not sufficiently robust for wide adoption. In many cases, the expense and specialized design of AUVs for particular tasks limits their applicability to a wider audience.In time-sensitive deployments, the robustness and task flexibility of ROVs means that they can be more readily deployed for a wider variety of tasks than autonomous systems (Murphy et al., 2012). J Field Robotics. 2019;36:495-516.wileyonlinelibrary.com/journal/rob

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Section: Research Applicationsmentioning

confidence: 99%

Shared autonomy for low‐cost underwater vehicles

Lawrance

DeBortoli

Jones

et al. 2018

Journal of Field Robotics

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“…Some examples are the "amigo mobility" scooter 3 and the adapted wheelchairs, 4 promoted by Egiro. 5 These products are, however, not particularly user-friendly. The user needs to first move into the mobility auxiliary device and then to learn how to use it (which may be particularly hard for the scooter case).…”

Section: Existing Solutionsmentioning

confidence: 99%

“…In [5], an anticipative shared control for robotic wheelchairs, targeted at people with disabilities, is presented. The same idea, of intelligent wheelchairs, is also the focus of the work in [6] where a data analysis system which provides an adapted command language is presented.…”

Section: Existing Solutionsmentioning

confidence: 99%

A Personal Robot as an Improvement to the Customers’ In- Store Experience

Campos¹,

Duarte²,

Pereira³

et al. 2018

Service Robots

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Robotics is a growing industry with applications in numerous markets, including retail, transportation, manufacturing, and even as personal assistants. Consumers have evolved to expect more from the buying experience, and retailers are looking at technology to keep consumers engaged. In today's highly competitive business climate, being able to attract, serve, and satisfy more customers is a key to success. It is our belief that smart robots will play a significant role in physical retail in the future. One successful example is wGO, 1 a robotic shopping assistant developed by Follow Inspiration. The wGO is an autonomous and self-driven shopping cart, designed to follow people with reduced mobility (the elderly, people in wheelchair, pregnant women, those with temporary reduced mobility, etc.) in commercial environments. With the Retail Robot, the user can control the shopping cart without the need to push it. This brings numerous advantages and a higher level of comfort since the user does not need to worry about carrying the groceries or pushing the shopping cart. The wGO operates under a vision-guided approach based on user-following with no need for any external device. Its integrated architecture of control, navigation, perception, planning, and awareness is designed to enable the robot to successfully perform personal assistance, while the user is shopping. Keywords: robotics, vision, retail, reduced mobility1 The robot is currently patent pending.

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“…The first control mode requires subjects to control the robot directly with BCI in the execution process. Without considering the autonomous control of the robot, the accuracy and the stability of these brain-controlled robotic systems cannot be guaranteed, and subjects will be under a lot of stress and mental burden when performing a task [18]. In contrast, the second control mode aims to combine human control and robotic autonomy during performing tasks.…”

Section: Introductionmentioning

confidence: 99%

Self-adaptive shared control with brain state evaluation network for human-wheelchair cooperation

Deng

Lin

et al. 2020

J. Neural Eng.

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Objective. For the shared control systems, how to trade off the control weight between robot autonomy and human operator is an important issue, especially for BCI-based systems. However, most of existing shared controllers have paid less attention to the effects caused by subjects with different levels of brain control ability. Approach. In this paper, a brain state evaluation network, termed BSE-NET, is proposed to evaluate subjects’ brain control ability online based on quantized attention-gated kernel reinforcement learning. With the output of BSE-NET (confidence score), a shared controller is designed to dynamically adjust the control weight between robot autonomy and human operator. Main results. The experimental results show that most of subjects achieved high and stable experimental success rate of approximately 90%. Furthermore, for subjects with different accuracy on EEG decoding, a proper confidence score can be dynamically generated to reflect their levels of brain control ability, and the proposed system can effectively adjust the control weight in all-time shared control. Significance. We discuss how our proposed method shows promise for BCI applications that can evaluate subjects’ brain control ability online as well as provide a method for the research on self-adaptive shared control to adaptively balance control weight between subject’s instruction and robot autonomy.

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Anticipative Shared Control for Robotic Wheelchairs Used by People with Disabilities

Cited by 10 publications

References 11 publications

Shared autonomy for low‐cost underwater vehicles

Shared autonomy for low‐cost underwater vehicles

A Personal Robot as an Improvement to the Customers’ In- Store Experience

Self-adaptive shared control with brain state evaluation network for human-wheelchair cooperation

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