An egocentric computer vision based co-robot wheelchair

Li, Haoxiang; Kutbi, Mohammed; Li, Xin; Cai, Changjiang; Mordohai, Philippos; Hua, Gang

doi:10.1109/iros.2016.7759291

Cited by 13 publications

(10 citation statements)

References 25 publications

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“…The image is then rotated to align with the mobile base frame and overlaid with an inflated grey path generated by the user's input commands (3). Finally, green circles are centred at coordinates where the grey path and obstacles intersect (4). image view of this information to relay back to the user visually via AR (presented in Section III-C).…”

Section: B Gridmap Processingmentioning

confidence: 99%

“…By augmenting the autonomy of the disabled community, assistive robots present one of the most promising avenues for helping reduce the burden on global healthcare services [1,2]. Within this domain of research, robotic wheelchairs have made impressive scientific advances through a wide range of unconventional input methods, such as brainmachine interfaces [3] and head motion [4], as opposed to traditional joystick control. Improvements in navigational assistance algorithms have also contributed to bettering usertechnology integration for powered mobility [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

“…The green patches (3) highlight objects that pose as potential collisions. The rear view display (4) captures the camera image mounted on the back of the seat (5), which includes overlaid graphics, such as the path and obstacle cues. The green and red directional arrows (6) represent the user's raw input and the corrected output, respectively.…”

Section: Introductionmentioning

confidence: 99%

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Head-Mounted Augmented Reality for Explainable Robotic Wheelchair Assistance

Zolotas

Elsdon

Demiris

2018

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Robotic wheelchairs with built-in assistive features, such as shared control, are an emerging means of providing independent mobility to severely disabled individuals. However, patients often struggle to build a mental model of their wheelchair's behaviour under different environmental conditions. Motivated by the desire to help users bridge this gap in perception, we propose a novel augmented reality system using a Microsoft Hololens as a head-mounted aid for wheelchair navigation. The system displays visual feedback to the wearer as a way of explaining the underlying dynamics of the wheelchair's shared controller and its predicted future states. To investigate the influence of different interface design options, a pilot study was also conducted. We evaluated the acceptance rate and learning curve of an immersive wheelchair training regime, revealing preliminary insights into the potential beneficial and adverse nature of different augmented reality cues for assistive navigation. In particular, we demonstrate that care should be taken in the presentation of information, with effort-reducing cues for augmented information acquisition (for example, a rear-view display) being the most appreciated.

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Section: B Gridmap Processingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Head-Mounted Augmented Reality for Explainable Robotic Wheelchair Assistance

Zolotas

Elsdon

Demiris

2018

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…In our previous work [27], we have presented a novel wheelchair control approach based on an egocentric camera. The key novelty in the design is that the wheelchair can be operated via the user's head motion, which is translated into the motion of a cursor on a tablet mounted in the user's field of view.…”

Section: Introductionmentioning

confidence: 99%

“…Since the required range of motion is limited, the amount of required effort is small, and no external forces are applied to the neck of the user. The wheelchair is also equipped with other sensors, primarily a consumer depth camera (Microsoft Kinect), which support autonomous and semi-autonomous navigation [8,28]. These functionalities, however, are not in scope here.…”

Section: Introductionmentioning

confidence: 99%

Usability Studies of an Egocentric Vision-Based Robotic Wheelchair

Kutbi

Xiaoxue

Chang

et al. 2020

J. Hum.-Robot Interact.

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Motivated by the need to improve the quality of life for the elderly and disabled individuals who rely on wheelchairs for mobility, and who may have limited or no hand functionality at all, we propose an egocentric computer vision based co-robot wheelchair to enhance their mobility without hand usage. The robot is built using a commercially available powered wheelchair modified to be controlled by head motion. Head motion is measured by tracking an egocentric camera mounted on the user's head and faces outward. Compared with previous approaches to hands-free mobility, our system provides a more natural human robot interface because it enables the user to control the speed and direction of motion in a continuous fashion, as opposed to providing a small number of discrete commands. This article presents three usability studies, which were conducted on 37 subjects. The first two usability studies focus on comparing the proposed control method with existing solutions while the third study was conducted to assess the effectiveness of training subjects to operate the wheelchair over several sessions. A limitation of our studies is that they have been conducted with healthy participants. Our findings, however, pave the way for further studies with subjects with disabilities. CCS Concepts: • Social and professional topics → Assistive technologies; • Computing methodologies → Computer vision; Computer vision tasks; • Human-centered computing → Interactive systems and tools;

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