Characterizing assistive shared control through vision-based and human-aware designs for wheelchair mobility assistance

Vishnu Karakkat Narayanan 1
1 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : Earliest records of a wheeled chair used to transport a person with disability dates back to the 6th century in China. With the exception of the collapsible X-frame wheelchairs invented in 1933, 1400 years of human scientific evolution has not radically changed the initial wheelchair design. Meanwhile, advancements in computing, and the development of artificial intelligence since the mid 1980s, has inevitably led to research on Intelligent Wheelchairs. Rather than focusing on improving the underlying design, the core objective of making a wheelchair intelligent is to make it more accessible. Even though the invention of the powered wheelchairs have partially mitigated a user's dependence on other people for their daily routines, some disabilities that affect limb movements, motor or visual coordination, make it impossible for a user to operate a common electrically powered wheelchair. Accessibility can also thus be thought of as the idea, where the wheelchair adapts to the user malady such that he/she is able to utilize its assistive capabilities to the fullest. While it is certain that intelligent robots are poised to address a growing number of issues in the service and medical care industries, it is important to resolve how humans and users interact with robots in order to accomplish common objectives. Particularly in the assistive intelligent wheelchair domain, preserving a sense of autonomy with the user is required, as individual agency is essential for his/her physical and social well being. This work thus aims to globally characterize the idea of assistive shared control while particularly devoting the attention to two issues within the intelligent assistive wheelchair domain viz. vision-based assistance and human-aware navigation. Recognizing the fundamental tasks that a wheelchair user may have to execute in indoor environments, we design low-cost vision-based assistance framework for corridor navigation. The framework provides progressive assistance for the tasks of safe corridor following and doorway passing. Evaluation of the framework is carried out on a robotised off-the-shelf wheelchair. From the proposed plug and play design, we infer an adaptive formulation for sharing control between user and robot. Furthermore, keeping in mind that wheelchairs are assistive devices that operate in human environments, it is important to consider the issue of human-awareness within wheelchair mobility. We leverage spatial social conventions from anthropology to surmise wheelchair navigation in human environments. Moreover, we propose a motion strategy that can be embedded on a social robot (such as an intelligent wheelchair) that allows it to equitably approach and join a group of humans in interaction. Based on the lessons learnt from the proposed designs for wheelchair mobility assistance, we can finally mathematically formalize adaptive shared control for assistive motion planning. In closing, we demonstrate this formalism in order to design a general framework for assistive wheelchair navigation in human environments.
Document type :
Complete list of metadatas

Cited literature [134 references]  Display  Hide  Download
Contributor : Vishnu Karakkat Narayanan <>
Submitted on : Thursday, April 20, 2017 - 10:05:54 AM
Last modification on : Friday, January 11, 2019 - 3:15:04 PM
Long-term archiving on : Friday, July 21, 2017 - 12:51:50 PM


  • HAL Id : tel-01426748, version 2


Vishnu Karakkat Narayanan. Characterizing assistive shared control through vision-based and human-aware designs for wheelchair mobility assistance . Robotics [cs.RO]. INRIA Rennes - Bretagne Atlantique; INSA Rennes, 2016. English. ⟨tel-01426748v2⟩



Record views


Files downloads