A Stochastic Control Strategy for Safely Driving a Powered Wheelchair

Teodorescu, Catalin Stefan; Zhang, Bingqing; Carlson, Tom

doi:10.1016/j.ifacol.2020.12.2741

Cited by 7 publications

(4 citation statements)

References 10 publications

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“…However, this technique incurs considerable computational cost to generate possible wheelchair trajectories, which may preclude its use in realtime applications. To circumvent this limitation, in [26], UCL's group proposed to use stochastic dynamic programming (SDP), which takes all the computation burden offline. The outcome is a lookup table that can be readily used online by the assist-as-needed algorithm.…”

Section: Model-based Shared Controlmentioning

confidence: 99%

See 1 more Smart Citation

Assistive Robotic Technologies for Next-Generation Smart Wheelchairs: Codesign and Modularity to Improve Users’ Quality of Life

Morbidi

Devigne²,

Teodorescu

et al. 2023

IEEE Robot. Automat. Mag.

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Section: Model-based Shared Controlmentioning

confidence: 99%

“…The outcome is a lookup table that can be readily used online by the assist-as-needed algorithm. More specifically, in [26], a model-based control architecture has been introduced to solve the obstacle avoidance problem. It consists of four blocks, where some are deterministic and others are stochastic.…”

Section: Model-based Shared Controlmentioning

confidence: 99%

Assistive Robotic Technologies for Next-Generation Smart Wheelchairs: Codesign and Modularity to Improve Users’ Quality of Life

Morbidi

Devigne²,

Teodorescu

et al. 2023

IEEE Robot. Automat. Mag.

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“…Here, we focus on the dynamics of the instrumented wheelchair from Fig. 2, which are governed by the following system equations [29]:…”

Section: Vehicle Modelmentioning

confidence: 99%

AssistMe: Policy iteration for the longitudinal control of a non-holonomic vehicle

Teodorescu¹,

Carlson²

2022

Preprint

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In this article we design a physically-inspired model-based assist-as-needed semi-autonomous control (ASC) algorithm to address the problem of safely driving a vehicle (a power wheelchair) in an environment with static obstacles. Once implemented online, the proposed algorithm requires limited computing power and relies on pre-computed (offline) maps (look-up tables). These are readily available by implementing policy iteration that minimizes the expected time to termination (safely stopping near an obstacle), by taking into account: (i) the vehicle dynamics; (ii) the drivers' intention modeled as three separate stochastic processes. We call them the expert driver, the naughty child and the blind driver models.A study with healthy participants confirmed that ASC outperforms a baseline rule-based control (a statistically significant result).

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“…[22]. Building on our previous work [23], the vehicle in Fig. 1 advancing in straight line is modeled as a point mass governed by the following dynamics:…”

Section: A Vehicle Modelmentioning

confidence: 99%

AssistMe: Using policy iteration to improve shared control of a non-holonomic vehicle

Teodorescu

Carlson

2022

2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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An assist-as-needed semi-autonomous control algorithm is designed to address the problem of safely driving a vehicle (a power wheelchair) in an environment with static obstacles. The main idea is to maximize the human driver's control experience while allowing them to navigate safely (the inputs do not lead to collisions). The proposed physicallyinspired model-based obstacle avoidance algorithm relies on optimal maps of the expected time for executing a safe stop manoeuvre. These maps are pre-computed using policy iteration in the case of an experienced driver stochastic model. As the burden of complex calculations is handled offline, the online implementation of the algorithm requires little computing resources. Its efficiency is tested experimentally in a study with healthy participants: a statistically significant result confirmed that the proposed algorithm outperforms a baseline rule-based control. A discussion with pros and cons ends this paper.

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A Stochastic Control Strategy for Safely Driving a Powered Wheelchair

Cited by 7 publications

References 10 publications

Assistive Robotic Technologies for Next-Generation Smart Wheelchairs: Codesign and Modularity to Improve Users’ Quality of Life

Assistive Robotic Technologies for Next-Generation Smart Wheelchairs: Codesign and Modularity to Improve Users’ Quality of Life

AssistMe: Policy iteration for the longitudinal control of a non-holonomic vehicle

AssistMe: Using policy iteration to improve shared control of a non-holonomic vehicle

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