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Workspace Aware Online Grasp Planning
TLDR
This work provides a framework for a workspace aware online grasp planner. Expand
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MAT: Multi-Fingered Adaptive Tactile Grasping via Deep Reinforcement Learning
TLDR
We present Multi-Fingered Adaptive Tactile Grasping, or MAT, a tactile closed-loop method capable of realizing grasps provided by a coarse initial positioning of the hand above an object. Expand
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Pixel-Attentive Policy Gradient for Multi-Fingered Grasping in Cluttered Scenes
TLDR
We introduce a multi-fingered robotic grasping policy in simulation that operates in the pixel space of the input: a single depth image. Expand
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Task level hierarchical system for BCI-enabled shared autonomy
TLDR
This paper describes a novel hierarchical system for shared control of a humanoid robot. Expand
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Generative Attention Learning: a "GenerAL" framework for high-performance multi-fingered grasping in clutter
TLDR
Generative Attention Learning (GenerAL) is a framework for high-DOF multi-fingered grasping that is not only robust to dense clutter and novel objects but also effective with a variety of different parallel-jaw and multi-fingerered robot hands. Expand
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Learning Precise 3D Manipulation from Multiple Uncalibrated Cameras
TLDR
We present an effective multi-view approach to closed-loop end-to-end learning of precise manipulation tasks that are 3D in nature. Expand
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Accelerated Robot Learning via Human Brain Signals
TLDR
We propose a method that uses evaluative feedback obtained from human brain signals measured via scalp EEG to accelerate RL for robotic agents in sparse reward settings. Expand
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Mobile Page Scanner
I. MOTIVATION Why wait to get a dedicated scanner when a mobile application can make you scan your document quickly? Specialized scanners are large effective means of converting hard officialExpand
Predicting Africa Soil Properties Using Machine Learning Techniques
Different machine learning algorithms were assessed for estimating five functional soil parameters (SOC content, Calcium content, Phosphorous content, sand content, and pH value). The algorithms usedExpand
Maximizing BCI Human Feedback using Active Learning
TLDR
We present an approach that uses active learning to smartly choose queries for the human supervisor based on the uncertainty of the robot and effectively reduces the amount of feedback needed to learn a given task. Expand