Online mining of human deep intention by proactive environment changes using deep neural networks

Er, Nur Baki
This thesis focuses on surfacing human deep intention, which is known or assumed, in a smart environment that consists of autonomous robotic systems which can interact with the human. Deep intentions are defined as kind of actions that humans would like to behave but pushed deeper in the stack of the intentions in a daily life. The purpose of the designed system is to observe the human in the smart room for a while and to analyze human’s behaviors to offer the optimal set of system behavior to surface a desired deep intention. Deep neural networks classify people implicitly by trained deep learning architecture and outputs the set of system behaviors to trigger deep intention. The autoencoders implemented in the network generate better and compressed representation of input vectors by creating feature vectors without using any feature extraction method. In addition autoencoders also enable the system to have better initialized parameters. This thesis work introduces our novel approach of surfacing human deep intention by utilizing human robot interaction in a smart environment.


Swarm robotics: From sources of inspiration to domains of application
Şahin, Erol (Springer Verlag; 2005-09-01)
Swarm robotics is a novel approach to the coordination of large numbers of relatively simple robots which takes its inspiration from social insects. This paper proposes a definition to this newly emerging approach by 1) describing the desirable properties of swarm robotic systems, as observed in the system-level functioning of social insects, 2) proposing a definition for the term swarm robotics, and putting forward a set of criteria that can be used to distinguish swarm robotics research from other multi-r...
Control of a mobile robot swarm via informed robots
Çelikkanat, Hande; Şahin, Erol; Department of Computer Engineering (2008)
In this thesis, we study how and to what extent a self-organized mobile robot flock can be guided by informing some of the robots within the flock about a preferred direction of motion. Specifically, we extend a flocking behavior that was shown to maneuver a swarm of mobile robots as a cohesive group in free space, avoiding obstacles. In its original form, this behavior does not have a preferred direction and the flock would wander aimlessly. In this study, we incorporate a preference for a goal direction i...
Face detection in active robot vision
Önder, Murat; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2004)
The main task in this thesis is to design a robot vision system with face detection and tracking capability. Hence there are two main works in the thesis: Firstly, the detection of the face on an image that is taken from the camera on the robot must be achieved. Hence this is a serious real time image processing task and time constraints are very important because of this reason. A processing rate of 1 frame/second is tried to be achieved and hence a fast face detection algorithm had to be used. The Eigenfa...
Performance in the Workplace: a Critical Evaluation of Cognitive Enhancement
Acartürk, Cengiz; Mücen, Barış (2022-04-01)
The popular debates about the future organization of work through artificial intelligence technologies focus on the replacement of human beings by novel technologies. In this essay, we oppose this statement by closely following what has been developed as AI technologies and analyzing how they work, specifically focusing on research that may impact work organizations. We develop this argument by showing that the recent research and developments in AI technologies focus on developing accurate and precise perf...
The learning and use of traversability affordance using range images on a mobile robot
Ugur, Emre; Dogar, Mehmet R.; Cakmak, Maya; Şahin, Erol (2007-04-14)
We are interested in how the concept of affordances can affect our view to autonomous robot control, and how the results obtained from autonomous robotics can be reflected back upon the discussion and studies on the concept of affordances. In this paper, we studied how a mobile robot, equipped with a 3D laser scanner, can learn to perceive the traversability affordance and use it to wander in a room filled with spheres, cylinders and boxes. The results showed that after learning, the robot can wander around...
Citation Formats
N. B. Er, “Online mining of human deep intention by proactive environment changes using deep neural networks,” M.S. - Master of Science, Middle East Technical University, 2015.