Electric power wheelchairs (EPWs) enhance the mobility capability of the elderly and the disabled, while the human-machine interaction (HMI) determines how well the human intention will be precisely delivered and how human-machine system cooperation will be efficiently conducted. A bibliometric quantitative analysis of 1154 publications related to this research field, published between 1998 and 2020, was conducted. We identified the development status, contributors, hot topics, and potential future research directions of this field. We believe that the combination of intelligence and humanization of an EPW HMI system based on human-machine collaboration is an emerging trend in EPW HMI methodology research. Particular attention should be paid to evaluating the applicability and benefits of the EPW HMI methodology for the users, as well as how much it contributes to society. This study offers researchers a comprehensive understanding of EPW HMI studies in the past 22 years and latest trends from the evolutionary footprints and forward-thinking insights regarding future research.
Orientation and Mobility training (O&M) is a specific program that teaches people with vision loss to orient themselves and travel safely within certain contexts. State-of-the-art research reveals that people with vision loss expect high-quality O&M training, especially at early ages, but the conventional O&M training methods involve tedious programs and require a high participation of professional trainers. However, there is an insufficient number of excellent trainers. In this work, we first interpret and discuss the relevant research in recent years. Then, we discuss the questionnaires and interviews we conducted with visually impaired people. On the basis of field investigation and related research, we propose the design of a training solution for children to operate and maintain direction based on audio augmented reality. We discuss how, within the perceptible scene created by EasyAR’s map-aware framework, we created an AR audio source tracing training that simulates a social scene to strengthen the audiometric identification of the subjects, and then to verify the efficiency and feasibility of this scheme, we implemented the application prototype with the required hardware and software and conducted the subsequential experiments with blindfolded children. We confirm the high usability of the designed approach by analyzing the results of the pilot study. Compared with other orientation training studies, the method we propose makes the whole training process flexible and entertaining. At the same time, this training process does not involve excessive economic costs or require professional skills training, allowing users to undergo training at home or on the sports ground rather than having to go to rehabilitation sites or specified schools. Furthermore, according to the feedback from the experiments, the approach is promising in regard to gamification.
This work introduces a high-performance, quadruped-assistive-robot expandable platform with wheel–leg mode transformation functions. The robot platform is designed for transporting goods in residential areas such as apartments, private houses, and office buildings. It is capable to move fast on flat ground on wheels or use legs to move in other places, especially for moving on and off residential staircases and wheelchair accessible ramps. To achieve higher load capacity and combine the knee joint with the drive wheel, we designed a compact torso–leg structure, driving the lower link through a ligament-like structure. Because the distance between the wheel and the torso is short, the mass centroid drops and the force arm caused by the load is reduced; the designed sample robot is capable to transport uniform mass loads up to 15 kg while keeping it affordable. The proposed ligament-like transmission structure also ensures the torso’s even gesture and load capability in its walking mode. Gait motion planning, finite element analysis, and task-oriented simulation have been conducted to prove its applicability and feasibility when given a heavy load to transport across flat and staired scenarios.
To improve the speed and position detection accuracy of surface-mount permanent magnet synchronous motor (SPMSM) vector control and reduce unnecessary chattering of the system, this paper proposes a sensorless control strategy of SPMSM based on an adaptive sliding mode observer (ASMO) with optimized phase-locked loop (OPLL) structure. First, in order to overcome the chattering of system caused by discontinuous switching characteristic of signum function in conventional sliding mode observer (CSMO), a continuous saturation function is selected as the switching function. The ASMO adopts the system state-related adaptive gain function to adjust the switching gain value of the system in real time, which overcomes the slow response speed or severe chattering of the system caused by the constant switching gain of CSMO. Second, to reduce the phase delay between the rotor position estimation value and the actual value caused by the adoption of low-pass filter (LPF) and the position estimation error caused by arctangent function method, an OPLL method is designed for accurate estimation of rotor position and speed. Finally, the effectiveness and feasibility of the proposed improved SMO algorithm is verified by simulation and experiments on an SPMSM with rated power of 2 kW.
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