Discriminating spatial intent from noisy joystick signals for wheelchair path planning and guidance

Kelilah L. Wolkowicz, Robert D. Leary, Jason Zachary Moore, Sean N. Brennan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

For patients with amyotrophic lateral sclerosis (ALS), disease progression can cause a loss of motor function. As motor function declines, the dexterity needed to control a wheelchair’s joysticks can also be compromised. The objective of this work is to integrate user sensor inputs and wheelchair position measurements to improve the performance of wheelchair guidance, even in the presence of noisy inputs from the user. This work evaluates probabilistic, model-based methods for blending joystick and position inputs along a series of user-created trajectories, similar to those that a wheelchair user may follow in their day-to-day navigational routines. We answer three key questions in order to associate joystick inputs to path-keeping decisions: 1) What is a path? 2) When are paths different? 3) What is the probability of a particular destination along a path? The algorithmic answers to these questions are verified using experimental wheelchair joystick and position measurements. Using this approach, the goal is to safely guide a wheelchair’s trajectory even if the user is providing ambiguous inputs. This process enables better discrimination of user joystick inputs for navigation algorithms, resulting in improved wheelchair guidance, safety, and patient monitoring.

Original languageEnglish (US)
Title of host publicationModeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control Systems; Unmanned Aerial Vehicles (UAVs) and Application; Unmanned Ground and Aerial Vehicles; Vibration in Mechanical Systems; Vibrations and Control of Systems; Vibrations
Subtitle of host publicationModeling, Analysis, and Control
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791851913
DOIs
StatePublished - Jan 1 2018
EventASME 2018 Dynamic Systems and Control Conference, DSCC 2018 - Atlanta, United States
Duration: Sep 30 2018Oct 3 2018

Publication series

NameASME 2018 Dynamic Systems and Control Conference, DSCC 2018
Volume3

Other

OtherASME 2018 Dynamic Systems and Control Conference, DSCC 2018
CountryUnited States
CityAtlanta
Period9/30/1810/3/18

Fingerprint

Wheelchairs
Motion planning
Position measurement
Trajectories
Patient monitoring
Navigation
Sensors

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

Cite this

Wolkowicz, K. L., Leary, R. D., Moore, J. Z., & Brennan, S. N. (2018). Discriminating spatial intent from noisy joystick signals for wheelchair path planning and guidance. In Modeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control Systems; Unmanned Aerial Vehicles (UAVs) and Application; Unmanned Ground and Aerial Vehicles; Vibration in Mechanical Systems; Vibrations and Control of Systems; Vibrations: Modeling, Analysis, and Control (ASME 2018 Dynamic Systems and Control Conference, DSCC 2018; Vol. 3). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DSCC2018-9228
Wolkowicz, Kelilah L. ; Leary, Robert D. ; Moore, Jason Zachary ; Brennan, Sean N. / Discriminating spatial intent from noisy joystick signals for wheelchair path planning and guidance. Modeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control Systems; Unmanned Aerial Vehicles (UAVs) and Application; Unmanned Ground and Aerial Vehicles; Vibration in Mechanical Systems; Vibrations and Control of Systems; Vibrations: Modeling, Analysis, and Control. American Society of Mechanical Engineers (ASME), 2018. (ASME 2018 Dynamic Systems and Control Conference, DSCC 2018).
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abstract = "For patients with amyotrophic lateral sclerosis (ALS), disease progression can cause a loss of motor function. As motor function declines, the dexterity needed to control a wheelchair’s joysticks can also be compromised. The objective of this work is to integrate user sensor inputs and wheelchair position measurements to improve the performance of wheelchair guidance, even in the presence of noisy inputs from the user. This work evaluates probabilistic, model-based methods for blending joystick and position inputs along a series of user-created trajectories, similar to those that a wheelchair user may follow in their day-to-day navigational routines. We answer three key questions in order to associate joystick inputs to path-keeping decisions: 1) What is a path? 2) When are paths different? 3) What is the probability of a particular destination along a path? The algorithmic answers to these questions are verified using experimental wheelchair joystick and position measurements. Using this approach, the goal is to safely guide a wheelchair’s trajectory even if the user is providing ambiguous inputs. This process enables better discrimination of user joystick inputs for navigation algorithms, resulting in improved wheelchair guidance, safety, and patient monitoring.",
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Wolkowicz, KL, Leary, RD, Moore, JZ & Brennan, SN 2018, Discriminating spatial intent from noisy joystick signals for wheelchair path planning and guidance. in Modeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control Systems; Unmanned Aerial Vehicles (UAVs) and Application; Unmanned Ground and Aerial Vehicles; Vibration in Mechanical Systems; Vibrations and Control of Systems; Vibrations: Modeling, Analysis, and Control. ASME 2018 Dynamic Systems and Control Conference, DSCC 2018, vol. 3, American Society of Mechanical Engineers (ASME), ASME 2018 Dynamic Systems and Control Conference, DSCC 2018, Atlanta, United States, 9/30/18. https://doi.org/10.1115/DSCC2018-9228

Discriminating spatial intent from noisy joystick signals for wheelchair path planning and guidance. / Wolkowicz, Kelilah L.; Leary, Robert D.; Moore, Jason Zachary; Brennan, Sean N.

Modeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control Systems; Unmanned Aerial Vehicles (UAVs) and Application; Unmanned Ground and Aerial Vehicles; Vibration in Mechanical Systems; Vibrations and Control of Systems; Vibrations: Modeling, Analysis, and Control. American Society of Mechanical Engineers (ASME), 2018. (ASME 2018 Dynamic Systems and Control Conference, DSCC 2018; Vol. 3).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Moore, Jason Zachary

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N2 - For patients with amyotrophic lateral sclerosis (ALS), disease progression can cause a loss of motor function. As motor function declines, the dexterity needed to control a wheelchair’s joysticks can also be compromised. The objective of this work is to integrate user sensor inputs and wheelchair position measurements to improve the performance of wheelchair guidance, even in the presence of noisy inputs from the user. This work evaluates probabilistic, model-based methods for blending joystick and position inputs along a series of user-created trajectories, similar to those that a wheelchair user may follow in their day-to-day navigational routines. We answer three key questions in order to associate joystick inputs to path-keeping decisions: 1) What is a path? 2) When are paths different? 3) What is the probability of a particular destination along a path? The algorithmic answers to these questions are verified using experimental wheelchair joystick and position measurements. Using this approach, the goal is to safely guide a wheelchair’s trajectory even if the user is providing ambiguous inputs. This process enables better discrimination of user joystick inputs for navigation algorithms, resulting in improved wheelchair guidance, safety, and patient monitoring.

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M3 - Conference contribution

AN - SCOPUS:85057372351

T3 - ASME 2018 Dynamic Systems and Control Conference, DSCC 2018

BT - Modeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control Systems; Unmanned Aerial Vehicles (UAVs) and Application; Unmanned Ground and Aerial Vehicles; Vibration in Mechanical Systems; Vibrations and Control of Systems; Vibrations

PB - American Society of Mechanical Engineers (ASME)

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Wolkowicz KL, Leary RD, Moore JZ, Brennan SN. Discriminating spatial intent from noisy joystick signals for wheelchair path planning and guidance. In Modeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control Systems; Unmanned Aerial Vehicles (UAVs) and Application; Unmanned Ground and Aerial Vehicles; Vibration in Mechanical Systems; Vibrations and Control of Systems; Vibrations: Modeling, Analysis, and Control. American Society of Mechanical Engineers (ASME). 2018. (ASME 2018 Dynamic Systems and Control Conference, DSCC 2018). https://doi.org/10.1115/DSCC2018-9228