Robot that Learns From Own Experience

dc.contributor.author	Azhar, Khadija
dc.date.accessioned	2023-08-18T10:38:22Z
dc.date.available	2023-08-18T10:38:22Z
dc.date.issued	2019
dc.identifier.other	172541
dc.identifier.uri	http://10.250.8.41:8080/xmlui/handle/123456789/36889
dc.description	Supervisor: Dr. Wajahat Hussain	en_US
dc.description.abstract	The robots can not be trained for all the unforeseen circumstances. How to act in a new environment? What is the purpose of the new object? Recently, it has been shown that robots can learn on the go by passively observing the human behaviour. What to do when there is no human present in the scene? The robot is expected to have a big database of observations related to his home. If the robot has seen the person sitting on a chair, in a classroom, can the robot predict what is the use of the neighbouring chair? If the person en ters/exits the room, through the door, can the robot predict the remaining entrances/exits in the same building? The man made scenes have repeatability. We propose to leverage this repeatability to transfer observations from one place to another.	en_US
dc.language.iso	en	en_US
dc.publisher	School of Electrical Engineering and Computer Science NUST SEECS	en_US
dc.title	Robot that Learns From Own Experience	en_US
dc.type	Thesis	en_US