Automatic Wheel Chair Control Using Eyeball Movement for Physically Challenged People

2012 ◽  
Vol 3 (3) ◽  
pp. 317-319
Author(s):  
R.Venkatesh R.Venkatesh ◽  
◽  
R.Karthick R.Karthick
Keyword(s):  
Wheel Chair ◽  
Physically Challenged

Regular perturbations to the motion of a three-wheeled mobile robot with the front-wheel drive under restricted state variables*

2020 ◽  
Author(s):  
Roman Chertovskih ◽  
Anna Daryina ◽  
Askhat Diveev ◽  
Dmitry Karamzin ◽  
Fernando L. Pereira ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Front Wheel ◽  
Wheeled Mobile Robot ◽  
State Variables ◽  
Wheel Drive

AUTOMATIC HEAD-MOVEMENT CONTROLLED WHEELCHAIR

2020 ◽  
Vol 9 (10) ◽  
pp. 62-67
Keyword(s):  
Head Movement ◽  
Motion Sensor ◽  
Electric Wheelchair ◽  
Wheel Chair ◽  
Head Band

This project is regarding the Motion controlled wheelchair for disabled. We are going to control motorized wheelchair using a head band having motion sensor and Arduino as controller. Problem: “often disabled who cannot walk find themselves being burden for their families or caretakers just for moving around the house. Disabled who are paralysed below head, who may not have functioning arms cannot control joystick controlled electric wheelchair.” This project is to solve their problem using a motion sensor to control their wheelchair. We are aiming towards building a more affordable, unique, low maintenance and available for all kind of head-controlled wheel chair.

scholarly journals Ground maneuver for front-wheel drive aircraft via deep reinforcement learning

2021 ◽  
Author(s):  
Hao Zhang ◽  
Zongxia Jiao ◽  
Yaoxing Shang ◽  
Xiaochao Liu ◽  
Pengyuan Qi ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Front Wheel ◽  
Wheel Drive

Establishment and comparison of a spatial dynamics model for virtual track train with different steering modes

2021 ◽  
pp. 146441932110240
Author(s):  
Zhonghui Yin ◽  
Jiye Zhang ◽  
Haiying Lu
Keyword(s):  
Pid Controller ◽  
Dynamic Performance ◽  
Spatial Dynamics ◽  
Steering System ◽  
Front Wheel ◽  
Proportional Integral Derivative ◽  
Dynamics Model ◽  
Proposed Model ◽  
Suspension Control ◽  
Curved Section

To solve the urbanization and the economic challenges, a virtual track train (VTT) transportation system has been proposed in China. To evaluate the dynamic behavior of the VTT, a spatial dynamics model has been developed that considers the suspension system and the steering system. Additionally, the model takes into account road irregularity to make simulations more realistic. Based on the newly proposed dynamic model and a designed proportional–integral–derivative (PID) controller, simulation frames of the vehicle and of the VTT are established with the path-tracking performance. The results show that the vehicle and the VTT can run along a desired lane with allowable errors, verifying the proposed model. The vehicle and VTT with the four-wheel steering system show a better dynamic performance than the models with the front-wheel steering system in the curved section. Moreover, the simulation frame can be further applied to dynamics-related assessments, parameter optimization and active suspension control strategy.

scholarly journals Coordination of Lateral Vehicle Control Systems Using Learning-Based Strategies

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1291
Author(s):  
Balázs Németh
Keyword(s):  
Control System ◽  
Control Systems ◽  
Coordinated Control ◽  
Front Wheel ◽  
Steering Angle ◽  
Conventional Model ◽  
Linear Parameter Varying ◽  
Coordination Strategy ◽  
Torque Vectoring ◽  
Performance Specifications

The paper proposes a novel learning-based coordination strategy for lateral control systems of automated vehicles. The motivation of the research is to improve the performance level of the coordinated system compared to the conventional model-based reconfigurable solutions. During vehicle maneuvers, the coordinated control system provides torque vectoring and front-wheel steering angle in order to guarantee the various lateral dynamical performances. The performance specifications are guaranteed on two levels, i.e., primary performances are guaranteed by Linear Parameter Varying (LPV) controllers, while secondary performances (e.g., economy and comfort) are maintained by a reinforcement-learning-based (RL) controller. The coordination of the control systems is carried out by a supervisor. The effectiveness of the proposed coordinated control system is illustrated through high velocity vehicle maneuvers.

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