Add to ORKG132 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2003.In addition to behavior learning, this dissertation initiates a novel research called automatic scene understanding by a robot, in which the robot is taught to learn scene semantics from multiple concept categories via the interactions with its world. A generic model for general-purpose scene understanding is presented, along with a case development for small-sized scene language understanding by a robot. The experimental result shows the effectiveness of the proposed method in solving the so-called "multilabeling" concept classification problems.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD
For robots to interact with humans at the language level, it becomes fundamental that robots and hum...
This thesis builds on the observation that robots, like humans, do not have enough experience to han...
Abstract—As robots are increasingly deployed in complex real-world domains, visual object recognitio...
132 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2003.In addition to behavior learn...
In order to behave autonomously, it is desirable for robots to have the ability to use human supervi...
In order to behave autonomously, it is desirable for robots to have the ability to use human supervi...
Schmüdderich J, Brandl H, Bolder B, et al. Organizing Multimodal Perception for Autonomous Learning ...
Abstract—This paper introduces a framework that allows a robot to form a single behavior–grounded ob...
Robust human-robot interaction in dynamic domains requires that the robot au-tonomously learn from s...
Abstract—This paper proposes a framework for learning human-provided category labels that describe i...
Many tasks that humans perform on a daily basis require the use of a container. For example, tool bo...
Dissertation presented at the Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa to ...
Abstract: Autonomous learning of objects using visual information is important to robotics as it can...
This paper presents a robotic vision system that can be taught to recognize novel objects in a semi-...
The use of social robots increased in the past few years. Current technology, however, lacks in depl...
For robots to interact with humans at the language level, it becomes fundamental that robots and hum...
This thesis builds on the observation that robots, like humans, do not have enough experience to han...
Abstract—As robots are increasingly deployed in complex real-world domains, visual object recognitio...
132 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2003.In addition to behavior learn...
In order to behave autonomously, it is desirable for robots to have the ability to use human supervi...
In order to behave autonomously, it is desirable for robots to have the ability to use human supervi...
Schmüdderich J, Brandl H, Bolder B, et al. Organizing Multimodal Perception for Autonomous Learning ...
Abstract—This paper introduces a framework that allows a robot to form a single behavior–grounded ob...
Robust human-robot interaction in dynamic domains requires that the robot au-tonomously learn from s...
Abstract—This paper proposes a framework for learning human-provided category labels that describe i...
Many tasks that humans perform on a daily basis require the use of a container. For example, tool bo...
Dissertation presented at the Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa to ...
Abstract: Autonomous learning of objects using visual information is important to robotics as it can...
This paper presents a robotic vision system that can be taught to recognize novel objects in a semi-...
The use of social robots increased in the past few years. Current technology, however, lacks in depl...
For robots to interact with humans at the language level, it becomes fundamental that robots and hum...
This thesis builds on the observation that robots, like humans, do not have enough experience to han...
Abstract—As robots are increasingly deployed in complex real-world domains, visual object recognitio...