Traded and combined cooperative control of a smart wheelchair

This article deals with a human–machine cooperative system for the control of a smart wheelchair for people with motor disabilities. The choice of a traded control mode is first argued. The paper then pursues two objectives. The first is to describe the design of the cooperative system by focusing on the dialogue and the interaction between the pilot and the robot. The second objective is to introduce a new cooperative mode. In this one, three features are proposed: two semi-autonomous features, a wall following and a doorway crossing, during which the user can intervene punctually to rectify a trajectory or a path, and an assisted mode where, conversely, the machine intervenes in a manual control to avoid obstacles. This mode of intervention of an entity, human or machine, supervising a movement controlled by the other is referred as “combined control.” Examples of scenarios exploiting the cooperative capabilities of the system are presented and discussed.

Development of an Autonomous Driving Smart Wheelchair for the Physically Weak

People who have difficulty moving owing to problems in walking spend their lives assisted by wheelchairs. In the past, research has been conducted regarding the application of various technologies to electric wheelchairs for user convenience. In this study, we evaluated a method of applying an autonomous driving function and developed an autonomous driving function using ROS. An electric wheelchair with a control unit designed to enable autonomous driving was used to test the basic performance of autonomous driving. The effectiveness of the technology was confirmed by comparing the results of autonomous driving with those of manual driving on the same route. It is expected that the evaluation and improvement of the usability and ride quality as well as additional studies will help improve the mobility convenience of physically disabled persons.

SMART WHEELCHAIR/VEHICLE FOR PHYSICALLY CHALLENGED PEOPLE WITH REVERSE GEAR OPERATION

This paper aims to design the vehicle for the physically challenged person with reverse gear system. This proposed vehicle helps them not to believe any third persons to require a reverse gear. Here we used \"tumbler gear” mechanism for our prototype where the gear is accustomed by changing the direction of gear. It contains two gears which place in parallel by changing their position with motor direction; that are often changed but in real time application we\'d wish to use ideal gear system with gear box. Also the bike contains ultrasonic sensor which supports echo signals to supply alert on taking reverse to avoid collision between other object. this technique also contains \"GPS\" which help their family to locate the position of the physically challenged person just easily. in case of any emergency, an ultrasonic sensor, GPS module and relay circuits are employed to drive the motor in our prototype.

Eyeball Movement Detection To Control Smart Wheelchair Using Eye Aspect Ratio (EAR)

Many developed technology's with an aim of helping the disabilities. One of them is a wheelchair. It is the most common stuff that used for helping disabilities as a tool for mobilization. There are two types of wheelchair. The first is the manual wheelchair, operated by hand. The second is an electrical wheelchair, that operated by joystick or other electric device. This research proposed a mechanism to control the wheelchair by using an eye movement. It could be used especially for people with multiple disabilities (hand and foot defects), so they can take an advantage of their eyeballs as a tool to control wheelchair movement. There are five options for controlling the wheelchair (leftward, rightward, upward, downward and center). Leftward, rightward and center used for control direction of smart wheelchair. Furthermore, upward and downward of eye movements used to control the speed of smart wheelchair. Upward command used to increase the speed. Meanwhile, down-ward used to decrease the speed (stop). The proposed method used EAR (Eye Aspect Ratio), which divided into three regions based on sector area, for determining the directions of the eyeball movement. EAR is the value that represents the ratio between the upper eyelid and lower eyelid. The result obtained high accuracy

A Novel IOT Based Smart Wheelchair Design for Cerebral Palsy Patients

Several patients face Cerebral Palsy. Such debilitating diseases impede motor control and make it difficult for them to operate traditional electric wheelchairs. Existing models of smart wheelchairs accommodate these issues to a certain extent but fail to deliver a solution for patients to use the wheelchairs completely autonomously. This paper proposes a novel model for a cost-effective smart wheelchair that takes simple gestures as input for movement, along with several quality-of-life and assistive modules such as vitals monitoring and voice memo support for patients suffering from memory loss, along with obstacle detection to ensure complete safety of the patient regardless of the terrain. The paper discusses the various modules present in the wheelchair, elaborates upon the algorithm used for input detection and calculation, and finally, the implementation of each module. Lastly, the paper enlists comparisons between existing smart wheelchair models and the proposed model and lists out its strengths, weaknesses and states its findings from the proposed system's results.

From HRI to CRI: Crowd Robot Interaction—Understanding the Effect of Robots on Crowd Motion

How does the presence of a robot affect pedestrians and crowd dynamics, and does this influence vary across robot type? In this paper, we took the first step towards answering this question by performing a crowd-robot gate-crossing experiment. The study involved 28 participants and two distinct robot representatives: A smart wheelchair and a Pepper humanoid robot. Collected data includes: video recordings; robot and participant trajectories; and participants’ responses to post-interaction questionnaires. Quantitative analysis on the trajectories suggests the robot affects crowd dynamics in terms of trajectory regularity and interaction complexity. Qualitative results indicate that pedestrians tend to be more conservative and follow “social rules” while passing a wheelchair compared to a humanoid robot. These insights can be used to design a social navigation strategy that allows more natural interaction by considering the robot effect on the crowd dynamics.