Optimizing the Nao robot path planning using digital twin implementation

نوع: Type: thesis

مقطع: Segment: masters

عنوان: Title: Optimizing the Nao robot path planning using digital twin implementation

ارائه دهنده: Provider: Fateme Daneshpajoh

اساتید راهنما: Supervisors: Dr mahdi abbasi

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: Dr hasan khotanlo_Dr hatam abdoli

زمان و تاریخ ارائه: Time and date of presentation: 2022

مکان ارائه: Place of presentation: virtual

چکیده: Abstract: Path planning and obstacle detection for robots is one of the important indicator in robotics, especially in humanoid robots. Advances in machine vision in the field of robotics have made it possible to automate the routing process. By automating the routing process for the robot using deep learning techniques, routing errors can be avoided and the accuracy and speed of obstacle detection can be increased. Automatic routing results also play an important role in robot movement in unknown paths and improve robot performance. On the one hand, due to the high computational complexity of machine learning algorithms and on the other hand, limited robot computing resources, digital twin design improves performance and Optimize resource usage. Digital twins that are part of the Internet of Things connect to the real world and provide information about their twin, improve performance, make changes, and thus become valuable. A digital twin is a digital representation of an object or physical system. In general, the digital twin reflects the current state of the object and is created and developed by the initial design of the product. The use of these digital twins can be very intelligent in the robot routing process and optimize resource utilization. Improving the accuracy and speed of route planning methods and detecting obstacles in mobile controllable robots is one of the goals of this project

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