Indoor and Outdoor Mobility for an Intelligent Autonomous Wheelchair

Lin, C. T.; Euler, Craig; Wang, Po-Jen; Mekhtarian, Ara

doi:10.1007/978-3-642-31534-3_26

Cited by 5 publications

(4 citation statements)

References 2 publications

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“…Similar to the findings of others' studies supporting the effectiveness of using wheelchair-mounted accelerometer data to classify the state of wheelchair motion (i.e., self vs. external propulsion) [25], [26], our findings indicate that a single frame-mounted IMU can capture terrain-specific features that are mainly unaffected by user-or maneuver-specific characteristics. In contrast to previously developed terrain classifiers relying on computationally extensive real-time imaging of the environment [27], our framework provides a computationally efficient and costeffective solution for terrain classification when using a wheelchair in certain environments. This is the first study to develop and evaluate the performance of learning-based and terrain-specific adaptive PAPAW controllers.…”

Section: Discussionmentioning

confidence: 99%

A Comparison Between Conventional and Terrain-Specific Adaptive Pushrim-Activated Power-Assisted Wheelchairs

Khalili

Kryt

Borisoff

2021

IEEE Trans. Neural Syst. Rehabil. Eng.

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Pushrim-activated power-assisted wheels (PAPAWs) are assistive technologies that provide ondemand propulsion assistance to wheelchair users. In this study, we aimed to develop an adaptive PAPAW controller that responds effectively to changes in environmental conditions (e.g., type of surface or terrain). Experiments were conducted to collect kinematics of wheelchair motion using a frame-mounted inertial measurement unit (IMU) while performing a variety of wheelchair activities on different indoor/outdoor terrains. Statistical characteristics of velocity and acceleration measurements were extracted and used to develop a terrain classification framework to identify certain indoor and outdoor terrains. The terrain classification framework, based on random forest classification algorithms and kinematic features, was implemented and tested in our laboratory-developed PAPAW. This computationally efficient terrain classification framework was successfully implemented and tested in real-time. The power-assist ratio of each wheel was adjusted based on the type of terrain (e.g., more assistance was provided on outdoor terrains). Our findings revealed that propulsion effort (e.g., peak input torque) on asphalt was significantly reduced when using adaptive controllers compared to conventional PAPAW controllers. In addition, subjective views of participants regarding the workload of wheelchair propulsion (e.g., physical/cognitive effort) supported the positive effects of adaptive PAPAW controllers. We believe that the adoption of terrain-specific adaptive controllers has the potential to improve the accessibility of outdoor terrains and to prevent or delay upper extremity joint degeneration or pain.

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Section: Discussionmentioning

confidence: 99%

A Comparison Between Conventional and Terrain-Specific Adaptive Pushrim-Activated Power-Assisted Wheelchairs

Khalili

Kryt

Borisoff

2021

IEEE Trans. Neural Syst. Rehabil. Eng.

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“…The type and placement of perception sensors on an EPW for smart wheelchair navigation can have a significant impact on the performance of the system as well as how the platform interacts with the wheelchair user. Some smart wheelchair designs favor sensor placement where the vehicle perception can be optimized but it impacts the EPW height and user access to the platform [10][11][12][13]. Newer developments in perception sensor technology can help to negate sensor placement limitations and reduce the impact of sensor placement on the platform accessibility [14,15].…”

Section: Related Workmentioning

confidence: 99%

“…Many self-driving wheelchair platforms use a laptop computer for onboard processing [12,13,16]. However, using only a single laptop computer can impose significant constraints on the real time processing capabilities of a smart wheelchair.…”

Section: Related Workmentioning

confidence: 99%

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Human-Machine Interface for a Smart Wheelchair

Hartman

Nandikolla

2019

Journal of Robotics

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The paper describes the integration of hardware and software with sensor technology and computer processing to develop the next generation intelligent wheelchair. The focus is a computer cluster design to test high performance computing for smart wheelchair operation and human interaction. The LabVIEW cluster is developed for real-time autonomous path planning and sensor data processing. Four small form factor computers are connected over a Gigabit Ethernet local area network to form the computer cluster. Autonomous programs are distributed across the cluster for increased task parallelism to improve processing time performance. The distributed programs operating frequency for path planning and motion control is 50Hz and 12.3Hz for 0.3 megapixel robot vision system. To monitor the operation and control of the distributed LabVIEW code, network automation is integrated into the cluster software along with a performance monitor. A link between the computer motion control program and the wheelchair joystick control of the drive train is developed for the computer control interface. A perception sensor array and control circuitry is integrated with the computer system to detect and respond to the wheelchair environment. Multiple cameras are used for image processing and scanning laser rangefinder sensors for obstacle avoidance in the cluster program. A centralized power system is integrated to power the smart wheelchair along with the cluster and sensor feedback system. The on board computer system is evaluated for cluster processing performance for the smart wheelchair, incorporating camera machine vision and LiDAR perception for terrain obstacle detection, operating in urban scenarios.

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The effect of robotic wheelchair control paradigm and interface on user performance, effort and preference: An experimental assessment

Erdoğan

Argall

2017

Robotics and Autonomous Systems

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Indoor and Outdoor Mobility for an Intelligent Autonomous Wheelchair

Cited by 5 publications

References 2 publications

A Comparison Between Conventional and Terrain-Specific Adaptive Pushrim-Activated Power-Assisted Wheelchairs

A Comparison Between Conventional and Terrain-Specific Adaptive Pushrim-Activated Power-Assisted Wheelchairs

Human-Machine Interface for a Smart Wheelchair

The effect of robotic wheelchair control paradigm and interface on user performance, effort and preference: An experimental assessment

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