Fuzzy Logic and Speech Recognition Applications on Autonomous Vehicles
Location
Nessmith-Lane Atrium
Session Format
Poster Presentation
Research Area Topic:
Engineering and Material Sciences - Mechanical
Abstract
Research work on robots, motion devices and vehicles has increased in the last few decades. Many of these are used to work in non-engineered or unstructured sites like lunar surfaces or hazardous waste sites. The robots that are created have been mobile and stationary and are made to minimize any harm to humans or go where a human cannot go.
A tele-operated robot can be created where the human operator would control every movement of the robot. However, it can be tiresome and fatiguing to the operator. Hence, autonomous robots, vehicles and motion devices have been created so they can perform a lot of tasks on their own, and the operator would have to control little of the vehicle’s movements. Artificial intelligence was created so that machines would show intelligent behavior. Later, researchers developed soft computing paradigms like neural networks, machine learning and fuzzy logic.
Control systems can be designed to control the height, speed, depth and/or direction of ground, unmanned aerial, and underwater vehicles. Yet, the control system that is developed can be affected by disturbances and noise. The disturbance and noise signals can affect the error signal, plant input and eventually the output. An example of disturbances could be a head wind for ground vehicle or a cross wind for the aerial vehicles. Researchers work to design robust control systems that will lessen the effects of the disturbances and noise.
There still could also be an operator that would control some of the vehicles’ movements through remote control or teleoperation. There is also research work where a vehicle would recognize voice and speech commands. The terms associated with this work are voice and speech recognition. It is basically where devices recognize voice commands while operating.
The goal of this research is to develop a system where a soft computing paradigm like fuzzy logic is used to create an autonomous vehicle. Then speech recognition would be added to the fuzzy logic control system and fuzzy decision-making techniques to increase the vehicle’s autonomy. It is hoped that the vehicle could perform even more tasks and be more flexible in its operation. With the added speech recognition, it is desired that the vehicle would have a more robust control system and not be as affected by the disturbances and noise signals.
While unmanned aerial vehicles have previously been the attention of this work, ground and unmanned underwater vehicles will be examined as well.
Presentation Type and Release Option
Presentation (Open Access)
Start Date
4-16-2016 2:45 PM
End Date
4-16-2016 4:00 PM
Recommended Citation
Smith, Earl, "Fuzzy Logic and Speech Recognition Applications on Autonomous Vehicles" (2016). GS4 Georgia Southern Student Scholars Symposium. 88.
https://digitalcommons.georgiasouthern.edu/research_symposium/2016/2016/88
Fuzzy Logic and Speech Recognition Applications on Autonomous Vehicles
Nessmith-Lane Atrium
Research work on robots, motion devices and vehicles has increased in the last few decades. Many of these are used to work in non-engineered or unstructured sites like lunar surfaces or hazardous waste sites. The robots that are created have been mobile and stationary and are made to minimize any harm to humans or go where a human cannot go.
A tele-operated robot can be created where the human operator would control every movement of the robot. However, it can be tiresome and fatiguing to the operator. Hence, autonomous robots, vehicles and motion devices have been created so they can perform a lot of tasks on their own, and the operator would have to control little of the vehicle’s movements. Artificial intelligence was created so that machines would show intelligent behavior. Later, researchers developed soft computing paradigms like neural networks, machine learning and fuzzy logic.
Control systems can be designed to control the height, speed, depth and/or direction of ground, unmanned aerial, and underwater vehicles. Yet, the control system that is developed can be affected by disturbances and noise. The disturbance and noise signals can affect the error signal, plant input and eventually the output. An example of disturbances could be a head wind for ground vehicle or a cross wind for the aerial vehicles. Researchers work to design robust control systems that will lessen the effects of the disturbances and noise.
There still could also be an operator that would control some of the vehicles’ movements through remote control or teleoperation. There is also research work where a vehicle would recognize voice and speech commands. The terms associated with this work are voice and speech recognition. It is basically where devices recognize voice commands while operating.
The goal of this research is to develop a system where a soft computing paradigm like fuzzy logic is used to create an autonomous vehicle. Then speech recognition would be added to the fuzzy logic control system and fuzzy decision-making techniques to increase the vehicle’s autonomy. It is hoped that the vehicle could perform even more tasks and be more flexible in its operation. With the added speech recognition, it is desired that the vehicle would have a more robust control system and not be as affected by the disturbances and noise signals.
While unmanned aerial vehicles have previously been the attention of this work, ground and unmanned underwater vehicles will be examined as well.
