Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 41 for “"Robot Learning"”.
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Robot learning from videos
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms
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Robot learning from videos
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms
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Robot learning with strong priors
Embedding learning ability in robotic systems is one of the long sought-after objectives of artificial intelligence research. Despite the recent advancements in hardware, large-scale machine learning algorithms and theoretical understanding of deep learning, it is still quite unrealistic to deploy …
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Compositional Robot Learning for Generalizable Interactions
… effectively and to interact safely with humans, robots must generalize their learned models to scenarios they have never been trained on before, such as new commands and new agents. Humans have shown a remarkable ability to compose concepts they have learned before in order to interpret and to …
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Managing learning interactions for collaborative robot learning
Robotic assistants should be able to actively engage their human partner(s) to generalize knowledge about relevant tasks within their shared environment. Yet a key challenge is not all human partners will be proficient at teaching; furthermore, humans should not be held accountable for tracking a …
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Robot Learning Assembly Tasks from Human Demonstrations
The industry robots are widely deployed in the assembly and production lines as they are efficient in performing highly repetitive tasks. They are mainly position-controlled and pre-programmed to work in well-structured environments. However, they cannot deal with dynamical changes and unexpected …
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An interactive toy robot: Learning through play
… no better substitute for being there when learning about the environment. While scientists are able to use sea robots to study and explore the ocean directly, most of us including children will never have this opportunity. So, finding other ways to educate and inspire children about the …
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Towards Scalable Robot Learning without Physical Robots
The development of generalist robots—capable of performing a wide range of tasks in diverse environments—requires large-scale datasets of robot interactions. Unlike language or vision domains, where data can be passively collected at scale, robotic data collection remains costly, labor-intensive, …
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Task-level robot learning on a complex task
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1989.
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Communication-Driven Robot Learning for Human-Robot Collaboration
The growing presence of modern learning robots necessitates a fundamental shift in design, as these robots must learn skills from human inputs. Two main components close the loop in a human-robot interaction: learning and communication. Learning derives robot behaviors from human inputs, and …
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Understanding the embodied teacher : nonverbal cues for sociable robot learning
As robots enter the social environments of our workplaces and homes, it will be important for them to be able to learn from natural human teaching behavior. My research seeks to identify simple, non-verbal cues that human teachers naturally provide that are useful for directing the attention of …
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Scalable and Generalizable Robot Learning: from Simulated to Real-World Applications
L'abstract è presente nell'allegato / the abstract is in the attachment
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Multi-fidelity Optimal Trajectory Generation: Optimal Experiment Design for Robot Learning
Data-driven methods have significantly advanced robot learning, yet their direct application to real-world robots remains challenging, particularly under extreme conditions. This challenge is especially pronounced for highly maneuverable vehicles like quadrotor aircraft, which often operate in …
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Exploring the Role of Foundation Models for Training Generalist Robot Learning Policies
… we explore two approaches to training generalist robot learning policies using large-scale foundation models. The first approach aims to use a video foundation model to generate task-conditioned synthetic demonstrations at scale from a single expert demonstration. The objective is to leverage …
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A Distributed Q-learning Classifier System for task decomposition in real robot learning problems
A distributed reinforcement-learning system is designed and implemented on a mobile robot for the study of complex task decomposition in real robot learning environments. The Distributed Q-learning Classifier System (DQLCS) is evolved from the standard Learning Classifier System (LCS) proposed by …
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Lifelong Personalization for Social Robot Learning Companions: Interactive Student Modeling Across Tasks and Over Time
… literacy skills are important foundations for learning and form the basis of later academic success. Motivated by a growing scientific consensus that language learning requires engaging students cognitively, affectively, and socially, this thesis advances work to develop “social robot learning …
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Robot Fleet Learning From Heterogeneous Data
One of the key roadblocks for training generalist robotic models today is heterogeneity. Previous robot learning methods often collect data to train with one specific embodiment for one task, which is expensive and prone to overfitting. Similar to humans, robots and embodied agents inherently have …
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Identifying Objects’ Inertial Parameters with Robotic Manipulation to Create Simulation-Ready Assets
… and scenes via real world data, allowing a robot to imagine future interactions with its environment. However, many existing approaches either do not consider the dynamics of objects being simulated or make assumptions about their mass distributions. In this work, we aim to make use of …
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Learning control of bipedal dynamic walking robots with neural networks
… performance requirements for a dynamic walking robot. Learning and adaptation can improve stability and robustness. This thesis explores such an adaptation capability through the use of neural networks. Three neural network models (BP, CMAC and RBF networks) are studied. The RBF network is …
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Generalizable Robot Manipulation through Unified Perception, Policy Learning, and Planning
Advancing robotic manipulation to achieve generalization across diverse goals, environments, and embodiments is a critical challenge in robotics research. While the availability of data and large-scale training has brought exciting progress in robotics manipulation, current methods often struggle …
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