| KEYWORD |
Gesture-Based Control of Robot Assistants for Enhanced Inclusivity in Manufacturing Industry
keywords COLLABORATIVE ROBOTICS, GESTURE RECOGNITION, INCLUSIVE MANUFACTURING
Reference persons DARIO ANTONELLI, ALESSANDRO SIMEONE
Thesis type EXPERIMENTAL
Description Abstract:
The integration of individuals with cognitive disabilities into the workforce remains a significant challenge in the manufacturing industry. The use of robot assistants provides a promising solution to this challenge, as they can assist individuals with cognitive disabilities in performing repetitive and complex tasks. One approach to improve the control of robot assistants is through gesture-based interfaces. This thesis proposes a research study on gesture-based control of robot assistants for enhancing inclusivity in the manufacturing industry. The study aims to investigate the effectiveness of gesture-based interfaces in controlling robot assistants and the potential benefits for workers with cognitive disabilities.
Methodology:
The proposed study will consist of two main parts. The first part will focus on the development of a gesture-based interface for controlling a robot assistant in a manufacturing environment. The interface will be designed to recognize simple and natural hand gestures, such as pointing or making a fist. The interface will be integrated with a robot assistant, which will be used to perform various tasks in a simulated manufacturing environment.
The second part of the study will focus on evaluating the effectiveness of the gesture-based interface for controlling the robot assistant. The study will involve testing the interface with a group of individuals with cognitive disabilities and comparing their performance with a control group that uses a traditional interface. The study will evaluate the efficiency, accuracy, and ease of use of the gesture-based interface.
Expected Outcomes:
The proposed study is expected to provide several outcomes. Firstly, it will contribute to the development of a gesture-based interface for controlling robot assistants, which could be used in various manufacturing settings. Secondly, it will provide insights into the effectiveness of the interface for enhancing inclusivity in the workplace, particularly for individuals with cognitive disabilities. Lastly, it will highlight the potential benefits of using robot assistants in manufacturing, particularly in terms of productivity and sustainability.
Conclusion:
This thesis proposes a research study on gesture-based control of robot assistants for enhanced inclusivity in manufacturing industry. The study aims to investigate the effectiveness of gesture-based interfaces in controlling robot assistants and the potential benefits for workers with cognitive disabilities. The proposed study will provide valuable insights into the development and application of robot assistants in manufacturing, particularly in terms of enhancing inclusivity and improving productivity.
Deadline 25/02/2024
PROPONI LA TUA CANDIDATURA