Haptic interfaces for wheelchair navigation in the built environment

A number of countries have recently introduced legislation aimed at ending discrimination against disabled people; in the United Kingdom the Disability Discrimination Act (1995) provides the disabled community with new employment and access rights. The intention of the act is to help those who rely on wheelchairs for mobility and who Frequently find that not all buildings provide conditions suited to easy access, Central to these new rights will be an obligation for employers and organizations to provide premises that do not disadvantage the disabled, This work reports on the development of instrumentation that allows wheelchair navigation within virtual buildings and can assist architects in identifying the needs of wheelchair users st an early design stage. Central to this project has been the need to provide a platform that can accommodate a range of wheelchair types and will map intended wheelchair motion into a virtual space. This interface must have the capacity to provide feedback to the user reflecting constraints present in the physical world, including changes in floor surface characteristics, gradients, and collisions. Integrating visual and nonvisual sensory feedback correlating to the physical effort of wheelchair propulsion has been found to augment the perception of self-motion within the virtual world and so can create an effective instrument for use in the study of wheelchair accessibility within the built environment, This project represents a collaborative effort between architects and bioengineers engaged in research related to platform design, construction, and interfacing, while testing and evaluation has been accomplished with the assistance of user groups

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

Master of Science

thesisThe objective of this research is to improve the ability of a human operator to drive an omnidirectional robot by using omnidirectional force-feedback. Omnidirectional vehicles offer improved mobility over conventional vehicles and can potentially benefit people requiring motorized transportation and industries where vehicles must operate in confined spaces. However, omnidirectional vehicles require more skill to control due to the additional degrees of freedom inherent in the vehicle’s design. We hypothesize that providing force-feedback to the driver through an omnidirectional joystick will allow the robot to assist the driver in navigating and avoiding collisions with obstacles in a manner that is natural to the operator. This research is the first attempt to use true omnidirectional 3-DOF (degree of freedom) force-feedback to provide navigational assistance for a human to drive an omnidirectional vehicle. While 2-DOF force-feedback has been used in a limited capacity for obstacle avoidance on omnidirectional vehicles, this is the first study to include a third rotational axis of force-feedback and use it to guide a driver along planar collision-avoiding trajectories with a natural coordination of orientation. Unique intellectual merits put forth by this research include use of a novel omnidirectional haptic device and force-feedback strategies to guide operators and experiments to quantify the ability of force-feedback to improve omnidirectional driving performance and driver experience in a real time scenario

Learning shared control by demonstration for personalized wheelchair assistance

An emerging research problem in assistive robotics is the design of methodologies that allow robots to provide personalized assistance to users. For this purpose, we present a method to learn shared control policies from demonstrations offered by a human assistant. We train a Gaussian process (GP) regression model to continuously regulate the level of assistance between the user and the robot, given the user's previous and current actions and the state of the environment. The assistance policy is learned after only a single human demonstration, i.e. in one-shot. Our technique is evaluated in a one-of-a-kind experimental study, where the machine-learned shared control policy is compared to human assistance. Our analyses show that our technique is successful in emulating human shared control, by matching the location and amount of offered assistance on different trajectories. We observed that the effort requirement of the users were comparable between human-robot and human-human settings. Under the learned policy, the jerkiness of the user's joystick movements dropped significantly, despite a significant increase in the jerkiness of the robot assistant's commands. In terms of performance, even though the robotic assistance increased task completion time, the average distance to obstacles stayed in similar ranges to human assistance