To date, self-driving experimental wheelchair technologies have been either inexpensive or robust, but not both. Yet, in order to achieve real-world acceptance, both qualities are fundamentally essential. We present a unique approach to achieve inexpensive and robust autonomous and semi-autonomous assistive navigation for existing fielded wheelchairs, of which there are approximately 5 million units in Canada and United States alone. Our prototype wheelchair platform is capable of localization and mapping, as well as robust obstacle avoidance, using only a commodity RGB-D sensor and wheel odometry. As a specific example of the navigation capabilities, we focus on the single most common navigation problem: the traversal of narrow doorways in arbitrary environments. The software we have developed is generalizable to corridor following, desk docking, and other navigation tasks that are either extremely difficult or impossible for people with upper-body mobility impairments.
A device for conveying and separating articles which are moved, while in engagement with each other, by an input conveyor and are transferred by a periodically operating transfer member onto an output conveyor which operates in synchronism with the transfer member and which engages the articles during their conveying movement and conveys them with a speed which is greater than the speed of the input conveyor. The transfer member is composed of a first pusher which moves transverse to the conveying direction for transferring each item from the output end of the input conveyor onto the output conveyor, and a second pusher which is driven independently of the first pusher for holding back the item immediately following the item being transferred until the first pusher returns to its starting position. This paper outlines the development of a navigation system to give semi-autonomous operation of wheelchairs. Our goal is to develop a navigation system that is commercially viable and capable of being retro-fitted to powered electric wheelchairs in the near future. We introduce our proposed system, and discuss the three crucial components of any autonomous semi-autonomous system: SLAM, obstacle avoidance, and path planning. Our system makes extensive use of freely available open-source software. Using The Player Project as the base framework, we use GMapping for mapping, Vector Field Histograms for obstacle avoidance, and Wavefront for path planning. Qualitative results are provided and discussed. In this paper, we present a system level approach to smart wheelchair system (SWS) navigation in urban environments. The proposed SWS ecosystem has two primary components: a mapping service which generates large-scale landmark maps, and the SWS vehicle itself, which is a client of the mapping service. The SWS prototype integrates 3D LIDAR imaging systems which provide robust perception in unstructured, outdoor environments. It also leverages these same sensors for map-based localization. In demonstrating the efficacy of the approach, the SWS navigated autonomously over a distance of more than 12 km in a representative urban environment without once losing localization, and without the use of GPS. This paper presents the architecture and implementation of a tele-presence wheelchair system based on tele-presence robot, intelligent wheelchair, and touch screen technologies. The tele-presence wheelchair system consists of a commercial electric wheelchair, an add-on tele-presence interaction module, and a touchable live video image based user interface (called TIUI). The tele-presence interaction module is used to provide video-chatting for an elderly or disabled person with the family members or caregivers, and also captures the live video of an environment for tele-operation and semi-autonomous navigation. The user interface developed in our lab allows an operator to access the system anywhere and directly touch the live video image of the wheelchair to push it as if he she did it in the presence. This paper also discusses the evaluation of the user experience. The works on Intelligent Wheelchairs (IW) have been an active research area in Assistive Technologies since its first prototypes in the 1980’s. But more than 30 years after that promising start almost none (but a few) of those prototypes reached their final users. This work will try to analyze the problems that maintain those vehicles in the labs, far from the real people. Among the possible reasons for that, two main issues are the availability of suitable sensors (in terms of cost and reliability) and over all the lack of an appropriate standard platform in the market to build up an IW. In this paper we will focus our analysis on the platform problem. Under our point of view, it is mandatory to reduce the cost of any IW proposal by using a common framework from the more basic to the most advanced systems. To reach that goal, our proposal for an Intelligent Wheelchair framework take advantage of using standard Electronics systems and Communication devices (USB, CAN, WiFi) in order to guarantee its compatibility with other electronic subsystems and services around the environment (i.e. location based services) and to be able to follow the continuous upgrade of such subsystems. In this paper, we present an approach to visual SLAM and human tracking for a wheelchair robot equipped with a Microsoft Kinect sensor that which is a novel sensing system that captures RGB and depth (RGB-D) images simultaneously. The speeded-up robust feature (SURF) algorithm is employed to provide the robust description of feature for environments and the target person from RGB images. Based on the environmental SURF features, we present the natural landmark based simultaneous localization and mapping with the extended Kalman filter suing RGB-D data. Meanwhile, a depth clustering based human detection is proposed to extract human candidates. Accordantly, the target person tracking is achieved with an online learned RGB-D appearance model by integrating histogram orientation of gradient descriptor, color, depth, and position information from the body of the identified caregiver. Moreover, a fuzzy based controller provides dynamical human following for the wheelchair robot with a desired interval. Consequently, the experimental results demonstrated the effectiveness and feasibility in real world environments.   Commercial electric-power wheelchairs have become much cheaper in the recent years, likewise the availability of reduced size sensors to an affordable price has made their integration easier in this kind of vehicle. This paper presents the development of a smart navigation system applied to an electric wheelchair. The developed work falls within the Ambient Assisted Living field (AAL), which includes all the technologies whose aim is to improve the quality of life of people in the home environment, especially for the elderly and physically impaired. In particular, the present work is focused on the development of technological support aimed at improving the daily life of that population segment who has motor difficulties, and is forced to use personal mobility support systems such as a wheelchair. This system is able to localize the wheelchair while it is moving in an indoor environment. The system exploits a low cost hardware and an integrated open source software, which permit a cheap integration with already available electric wheelchairs. Reliable autonomous navigation is an active research topic that has drawn the attention for decades, however, human factors such as navigational comfort has not received the same level of attention. This work proposes the concept of “comfortable map” and presents a navigation approach for autonomous passenger vehicles which in top of being safe and reliable is comfortable. In our approach we first extract information from users preference related to comfort while sitting on a robotic wheelchair under different conditions in an indoor corridor environment. Human-comfort factors are integrated to a geometric map generated by SLAM framework. Then a global planner computes a safe and comfortable path which is followed by the robotic wheelchair. Finally, an evaluation with 29 participants using a fully autonomous robotic wheelchair, showed that more than 90 of them found the proposed approach more comfortable than a shortest-path state of the art approach. Many people who are mobility impaired are, for a variety of reasons, incapable of using an ordinary wheelchair. In some instances, a power wheelchair also cannot be used, usually because of the difficulty the person has in controlling it (often due to additional disabilities). This paper describes two low-cost robotic wheelchair prototypes that assist the operator of the chair in avoiding obstacles, going to pre-designated places, and maneuvering through doorways and other narrow or crowded areas. These systems can be interfaced to a variety of input devices, and can give the operator as much or as little moment by moment control of the chair as they wish. This paper describes both systems, the evolution from one system to another, and the lessons learned. In this paper, we explore the use of synthesized landmark maps for absolute localization of a smart wheelchair system outdoors. In this paradigm, three-dimensional map data are acquired by an automobile equipped with high precision inertial GPS systems, in conjunction with light detection and ranging (LIDAR) systems, whose range measurements are subsequently registered to a global coordinate frame. The resulting map data are then synthesized a priori to identify robust, salient features for use as landmarks in localization. By leveraging such maps with landmark meta-data, robots possessing far lower cost sensor suites gain many of the benefits obtained from the higher fidelity sensors, but without the cost.We show that by using such a map-based localization approach, a smart wheelchair system outfitted only with a 2-D LIDAR and encoders was able to maintain accurate, global pose estimates outdoors over almost 1 km paths. In this paper, a robotic wheelchair using only a pan-tilt-zoom camera is proposed for developing a robotic system which enables a user to navigate in complex environment at low cost. For realizing the proposed system, a high accuracy visual marker, LentiBar which is capable of achieving a high level of precision in positioning and orienting a robotic wheelchair is utilized and its application to door crossing for a robotic wheelchair is presented. Since the visual marker is attached on the top of the target door through which the wheelchair is going to pass, the typical problems for achieving geometric features of the environment can be easily addressed. Door crossing navigation methods are also explained, which enable automatic and hybrid navigation of the robotic wheelchair. Finally, experimental results show the feasibility of the proposed navigation method and the robotic wheelchair system. In the present work, a robotic wheelchair navigation system which is specially designed for confined spaces is proposed. In confined spaces, the movements of wheelchairs are restricted by the environment more than other unicycle type vehicles. For example, if the wheelchair is too close to a wall, it can not rotate freely because the front or back may collide with the wall. The navigation system is composed by a path planning module and a control module; both use the environment and robot information provided by a SLAM algorithm to attain their objectives. The planning strategy uses the Monte Carlo technique to find a minimum path within the confined environment and takes into account the variance propagation in the predicted path for ensuring the safe driving of the robot. The objective of the navigation system is to drive the robotic wheelchair within the confined environment in order to reach a desired orientation or posture.