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Skip to Search Results- 16Robotics
- 2Computer Vision
- 2Reinforcement learning
- 1Appearance-based SLAM
- 1Artificial intelligence
- 1Assistive Robotics
- 2Parker, Christopher A. C.
- 1Akturk, Sait
- 1Hajebi, Kiana
- 1Hernandez Herdocia, Alejandro
- 1Jiang, Chen
- 1Johnstonbaugh, Kerrick
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Spring 2023
Choosing an appropriate action representation is an integral part of solving robotic manipulation problems. Published approaches include latent action models, which train context-conditioned neural networks to map lowdimensional latent actions to high-dimensional actuation commands. Such models...
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Spring 2023
Wheelchair-mounted robotic manipulators have the potential to help the elderly and individuals living with disabilities carry out their activities of daily living independently. While robotics researchers focus on assistive tasks from the perspective of various control schemes and motion types, ...
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Back2Future-SIM: Creating Real-Time Interactable Immersive Virtual World For Robot Teleoperation
DownloadSpring 2024
In the context of human-robot interaction (HRI), robot autonomy addresses how environmental input influences a robot’s actions, spanning a spectrum from full human control to independent robot motion. The quality of HRI relies on information exchange, evaluated through factors like interaction...
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Collective decision-making in decentralized multiple-robot systems: a biologically inspired approach to making up all of your minds
DownloadFall 2009
Decision-making is an important operation for any autonomous system. Robots in particular must observe their environment and compute appropriate responses. For solitary robots and centralized multiple-robot systems, decision-making is a relatively straightforward operation, since only a single...
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Decision Frequency Adaptation in Reinforcement Learning Using Continuous Options with Open-Loop Policies
DownloadFall 2023
In classic reinforcement learning(RL) for continuous control, agents make decisions at discrete and fixed time intervals. The duration between decisions becomes a crucial hyperparameter. Setting it too short may increase the problem’s difficulty by requiring the agent to make numerous decisions...
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Fall 2015
Understanding how an artificial agent may represent, acquire, update, and use large amounts of knowledge has long been an important research challenge in artificial intelligence. The quantity of knowledge, or knowing a lot, may be nicely thought of as making and updat- ing many predictions about...
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Fall 2015
Simultaneous localization and mapping (SLAM) in an unknown environment is a prerequisite to have a truly autonomous mobile robot. In this thesis, we focus on appearance-based visual SLAM, for which we develop a graph-based nearest-neighbor search algorithm to speed up bag-of-words (BoW) image...
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Highway Lane change under uncertainty with Deep Reinforcement Learning based motion planner
DownloadSpring 2020
Motion Planning is a fundamental component of a mobile robot to reach its goal safely avoiding collision. For a self-driving car on a highway, the presence of non-communicating vehicles, specially those whose intent is unknown, creates a lot of uncertainty for the motion planner in generating a...
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Fall 2011
This thesis addresses the problem of automatic real-time 3D reconstruction of general scenes from monocular video. Whereas many impressively accurate reconstruction techniques exist in the multi-view stereo literature, most are slow offline batch methods designed to work in highly calibrated...