Non-Metrical Navigation Through Visual Path Control

We describe a new method for wide-area, non-metrical robot navigationwhich enables useful, purposeful motion indoors. Our method has twophases: a training phase, in which a human user directs a wheeledrobot with an attached camera through an environment while occasionallysupplying textual place names; and a navigation phase in which theuser specifies goal place names (again as text), and the robot issueslow-level motion control in order to move to the specified place. We show thatdifferences in the visual-field locations and scales of features matched acrosstraining and navigation can be used to construct a simple and robust controlrule that guides the robot onto and along the training motion path.Our method uses an omnidirectional camera, requires approximateintrinsic and extrinsic camera calibration, and is capable of effective motioncontrol within an extended, minimally-prepared building environment floorplan.We give results for deployment within a single building floor with 7 rooms, 6corridor segments, and 15 distinct place names

Kinect based Intelligent Wheelchair navigation with potential fields

Increasing elderly people population and people with disabilities constitute a huge demand for wheelchairs. Wheelchairs have an important role on improving the lives and mobilization of people with disabilities. Moreover, autonomous wheelchairs constitute a suitable research platform for academic and industrial researchers. In this study, Finite state machine (FSM) based high-level controller and Kinect based navigation algorithm have been developed for ATEKS (Intelligent Wheelchair) which has high-tech control mechanisms, low-cost sensors and open source software (ROS, GAZEBO, ANDROID). © 2014 IEEE

An Adaptive Guidance System for Robotic Walking Aids

In the last years, several robotic walking aids to assist elderly users with mobility constraints and thus to react to the growing number of elderly persons in our society have been developed. In order to ensure good support for the user, the robotic walker should adapt to the motion of the user while at the same time not losing the target out of sight. Even though some of the existing active robotic walkers are able to guide their user to a target, during guidance, the input of the user is not considered sufficiently. Therefore a new adaptive guidance system for robotic walkers has been developed. It is able to lead the walking aid user to a given target while considering his inputs during guidance and adapting the path respectively. The guidance system has been implemented on the mobile robot assistant Care-O-bot II and a field test was done in an old people’s residence proving the correct function and usefulness of the guidance system

Brain-coupled Interaction for Semi-autonomous Navigation of an Assistive Robot

This paper presents a novel semi-autonomous navigation strategy designed for low throughput interfaces. A mobile robot (e.g. intelligent wheelchair) proposes the most probable action, as analyzed from the environment, to a human user who can either accept or reject the proposition. In case of refusal, the robot will propose another action, until both entities agree on what needs to be done. In an unknown environment, the robotic system first extracts features so as to recognize places of interest where a human-robot interaction should take place (e.g. crossings). Based on the local topology, relevant actions are then proposed, the user providing answers by the mean of a button or a brain-computer interface (BCI). Our navigation strategy is successfully tested both in simulation and with a real robot, and a feasibility study for the use of a BCI confirms the potential of such interface

Development of an elastic path controller for collaborative robot

Master'sMASTER OF ENGINEERIN

A Brain Controlled Wheelchair to Navigate in Familiar Environments

Ph.DDOCTOR OF PHILOSOPH

Autonomous wheelchair with a smart driving mode and a Wi-Fi positioning system

Wheelchairs are an important aid that enhances the mobility of people with several types of disabilities. Therefore, there has been considerable research and development on wheelchairs to meet the needs of the disabled. Since the early manual wheelchairs to their more recent electric powered counterparts, advancements have focused on improving autonomy in mobility. Other developments, such as Internet advancements, have developed the concept of the Internet of Things (IoT). This is a promising area that has been studied to enhance the independent operation of the electrical wheelchairs by enabling autonomous navigation and obstacle avoidance. This dissertation describes shortly the design of an autonomous wheelchair of the IPL/IT (Instituto Politécnico de Leiria/Instituto de Telecomunicações) with smart driving features for persons with visual impairments. The objective is to improve the prototype of an intelligent wheelchair. The first prototype of the wheelchair was built to control it by voice, ocular movements, and GPS (Global Positioning System). Furthermore, the IPL/IT wheelchair acquired a remote control feature which could prove useful for persons with low levels of visual impairment. This tele-assistance mode will be helpful to the family of the wheelchair user or, simply, to a health care assistant. Indoor and outdoor positioning systems, with printed directional Wi-Fi antennas, have been deployed to enable a precise location of our wheelchair. The underlying framework for the wheelchair system is the IPL/IT low cost autonomous wheelchair prototype that is based on IoT technology for improved affordability