Robotic Wheelchair System Research Articles

Research on the shared control technology for robotic wheelchairs based on topological map

PurposeA robotic wheelchair system was designed to assist disabled people with disabilities to walk.Design/methodology/approachAn anticipated sharing control strategy based on topological map is proposed in this paper, which is used to assist robotic wheelchairs to realize interactive navigation. Then, a robotic wheelchair navigation control system based on the brain-computer interface and topological map was designed and implemented.FindingsIn the field of robotic wheelchairs, the problems of poor use, narrow application range and low humanization are still not improved.Originality/valueIn the system, the topological map construction is not restricted by the environment structure, which helps to expand the scope of application; the shared control system can predict the users’ intention and replace the users’ decision to realize human-machine interactive navigation, which has higher security, robustness and comfort.

An enhanced latent semantic indexing with term frequency-inverse document frequency variant for software traceability

This paper proposes an improved Latent Semantic Indexing (LSI) with Term Frequency-Inverse Document Frequency (TFIDF) variant for software traceability. The main advantage of the method is the simplicity and accuracy of the algorithm such that it can produce high precision and recall. The accuracy of tracing precise links between software artefacts is achieved by feeding the LSI with TF-IFDF variant that halves the TF and IDF values, thus increases the probability of yielding precise links. To test the accuracy of the proposed method, two case studies were evaluated, namely Mushroom Management System (MMS) and Robotic Wheelchair System (RWS). The superiority of the proposed method over a conventional LSI is confirmed by 409.09%, 900.00%, and 620.00% improvements for precision, recall, and harmonic mean scores, respectively, in MMS case study, at cosine threshold of 0.94. It is anticipated that the method could be beneficial in the design of a practical and accurate system for retrieving precise software traceability links.

Technique for Early Reliability Prediction of Software Components Using Behaviour Models.

Behaviour models are the most commonly used input for predicting the reliability of a software system at the early design stage. A component behaviour model reveals the structure and behaviour of the component during the execution of system-level functionalities. There are various challenges related to component reliability prediction at the early design stage based on behaviour models. For example, most of the current reliability techniques do not provide fine-grained sequential behaviour models of individual components and fail to consider the loop entry and exit points in the reliability computation. Moreover, some of the current techniques do not tackle the problem of operational data unavailability and the lack of analysis results that can be valuable for software architects at the early design stage. This paper proposes a reliability prediction technique that, pragmatically, synthesizes system behaviour in the form of a state machine, given a set of scenarios and corresponding constraints as input. The state machine is utilized as a base for generating the component-relevant operational data. The state machine is also used as a source for identifying the nodes and edges of a component probabilistic dependency graph (CPDG). Based on the CPDG, a stack-based algorithm is used to compute the reliability. The proposed technique is evaluated by a comparison with existing techniques and the application of sensitivity analysis to a robotic wheelchair system as a case study. The results indicate that the proposed technique is more relevant at the early design stage compared to existing works, and can provide a more realistic and meaningful prediction.

Maintaining Formation of Multiple Robotic Wheelchairs for Smooth Communication

To meet the demands of an aging society, research on intelligent/robotic wheelchairs have been receiving a lot of attention. In elderly care facilities, care workers are required to communicate with the elderly in order to maintain both their mental and physical health. While this is regarded as important, having a conversation with someone on a wheelchair while pushing it from behind in a traditional setting would interfere with their smooth and natural conversation. So we are developing a robotic wheelchair system which allows companions and wheelchair users to move in a natural formation. This paper reports on an investigation to learn the patterns of human behavior when the wheelchair users and their companions communicate while walking together. The ethnographic observation reveals a natural formation of positioning for both companions and wheelchair users. Based on this investigation, we propose a multiple robotic wheelchair system which can maintain desirable formations for communication between wheelchairs.

Path Planning under Interface-Based Constraints for Assistive Robotics

We present a heuristic-based search method for path planning in shared human-robot control scenarios in which the robot should adhere to specific motion constraints imposed by the human's control interface. This approach to path planning gives special consideration to kinematic and dynamic constraints introduced to reconcile discrepancies between the control space of the user and the control space of the robot. The resulting paths more closely mirror paths produced by users of the same interface; which is helpful, for example, when inferring human intent or for control sharing. Our first insight is to develop a hierarchical finite state machine describing the constrained state space, state transitions and associated costs. We then use this definition to embed the constraints of the interface into our heuristic planning algorithm, named C*, with simple modifications to the A*/D* family of graph search algorithms. This approach allows us to maintain powerful theoretical guarantees such as complexity and completeness. In this paper, we ground our augmented path planning algorithm with an implementation on a robotic wheelchair system and a Sip-and-Puff interface. We demonstrate that the new approach produces paths and control signals that more closely resemble user-generated data and can easily be incorporated into real hardware systems.

A Low Cost Robotic Wheelchair System Using a Pan-Tilt Camera and a Visual Marker

In this paper, a low cost robotic wheelchair system with only a pan-tilt camera is explained. In order to reduce the development cost, an electric wheelchair using a visual marker which is capable of achieving a high level of precision in positioning an electric wheelchair without geometric features is proposed. Then, indoor navigation methods are explained, which enable automatic and hybrid navigation of an electric wheelchair with only a pan-tilt camera. Finally, experiment results obtained by considering a particular scenario for indoor navigation reveal the feasibility of the proposed robotic wheelchair system.

English

Many people those using wheelchairs are not able to control an electronic wheelchair with joystick interface. The iWheel robotic wheelchair system is a general purpose navigational assistant in environments that are accessible for the disabled (e.g., ramps and doorways of sufficient width to allow a wheelchair to pass). A reactive system does not use maps for navigation. One of the advantages of this strategy is that users can navigate in multiple locations and environments. This report describes indoor navigation in the iWheel system; outdoor navigation is currently under development.

A robotic intelligent wheelchair system based on obstacle avoidance and navigation functions

Powered wheelchairs offer a means of independent mobility for older adults and patients who are unable to walk and cannot propel a manual wheelchair. One concern is these adults and patients are unable to drive a powered wheelchair safely or properly. Intelligent wheelchairs offer an approach to address this problem by self-controlling the movement and direction of the wheelchair without patients and older adult's intervention. This paper describes the development and evaluation of a robotic intelligent wheelchair system (RIWS) based on obstacle avoidance and navigation functions that allow patients to navigate to scheduled outpatient appointments in a hospital safely and accurately. Experimental results show that all scheduled destinations were successfully reached by our RIWS.

顔の視覚情報処理を用いた知的車椅子

With the increase in the number of senior citizens, there has been a growing demand for human-friendly wheelchairs as mobility aids. This paper proposes the concept of an intelligent wheelchair to meet this need. It can understand human intentions by observing the user's nonverbal behaviors and can move as the user wishes with minimal human operations. It also describes our experimental robotic wheelchair system. Human intentions appear most on his/her face. Thus, the experimental system observes the human face, computing the direction of the face. As the first step toward the intelligent wheelchair, we have performed experiments on controlling the system's motion according to the direction of the face. Experimental results prove our approach promising.