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 11 of 11 for “"Intent Recognition"”.
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Intent Recognition in Multi-Agent Domains
Intent recognition is an extremely important aspect of social robotics. The ability to recognize and react to intentions is not only an integral part of social interaction, but is also useful in adversarial domains, as discussed in this thesis. It is especially important to be capable of performing …
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Multimodal intent recognition for natural human-robotic interaction
… posed for this work were as follows: Can speech recognition and techniques for topic spotting be used to identify spoken intent in unconstrained natural speech? Can gesture recognition systems based on statistical speech recognition techniques be used to bridge the gap between physical movements …
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Person Profiles and Sensor Calibration for Intent Recognition in Socially Aware Navigation
Earlier work in the field of intent recognition used laser and cameras to track people and extract physical information to train and test models of intention. With the progression of computation abilities, Neural Networks have made it possible to extract additional information that earlier work was …
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Risk-bounded coordination of human-robot teams through concurrent intent recognition and adaptation
… be able to (1) recognize their human teammate's intentions, and (2) automatically adapt to those intentions in an intelligent manner. This thesis makes progress in these areas by proposing a framework that solves these two problems (task-level intent recognition and robotic adaptation) …
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Models of Intention for Human-Robot Interaction
… interaction is the process of inferring humans' intentions from their observed behavior. In this dissertation, we define the "intent recognition problem" in robotics, describing what it is and why it matters. We then describe a series of systems that we have designed and deployed on several …
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Robust and Scalable Multiagent Reinforcement Learning in Adversarial Scenarios
… adversarial scenarios due to the unknown agent intents and unexpected, possibly adversarial behaviors. This thesis presents approaches for robust and scalable multiagent learning with the goal of efficiently building autonomous agents that can operate robustly in adversarial scenarios. The …
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An inertial measurement-based gait detection system for active leg prostheses
… These data are then processed using an intent recognition method based on a hybrid discrete-continuous physical model of human walking. This method is evaluated for accuracy and robustness for real-time use.
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Unsupervised learning and recognition of physical activity plans
… the agent to anticipate and adapt to human intent. In the future, more robots may be deployed in situations that require collaboration with humans, such as scientific exploration, search and rescue, hospital assistance, and even domestic care. These situations require robots to work together …
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The Development and Utilization of Tandem Fluency in Human-Exoskeleton Interaction
… especially for non-cyclic motions, disrupt user intent and movement, often offering no benefit, or even causing harm by increasing discomfort and injury risk. This lack of fluency is frequently linked to poor intent recognition and absence of predictive control. To address this, we propose …
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Generalized Task Structure Learning for Collaborative Multi-Robot/Human-Robot Task Allocation
… for a more robust task execution. Lastly, an intent recognition system was incorporated into the architecture to allow for human-robot teams to work collaboratively on a task.Each of these extensions were validated separately through several experiments utilizing either multi-robot or …
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Goal-directed planning and plan recognition for the sustainable control of homes
… planning, which addresses comfort, and (2) intent recognition, which supports ease of use. Goal-direction improves efficiency by specifying what energy consuming activities the users need and when, and enables peak demand to be reduced by specifying the flexibility that the user has with …