Cognitive Robotics
Endowing a robot with intelligent behavior by providing it with a processing architecture that allows it to learn and reason about how to behave in response to complex goals in a complex world. Cognitive robots integrate perception, cognition and action.
Videos
Cognitive Robotics Playlist
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Extremum Seeking Controlled Wiggling for Tactile Insertion
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FeelAnyForce: Estimating Contact Force Feedback from Tactile Sensation
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AcTExplore: Active Tactile Exploration on Unknown Objects
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VAIolin — Music Education for All
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Autonomous Social Distancing in Urban Environments using a Quadruped Robot
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COVID-Robot: Monitoring Social Distancing Constraints in Crowded Scenarios
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Crowd-Steer: Smooth and Collision-Free Navigation in Dense Scenarios Using High-Fidelity Simulation
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ProxEmo: Gait-based Emotion Learning and Multiview Proxemic Fusion for Social-Aware Robot Navigation
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GraphRQI: Classifying Driver Behaviors Using Graph Spectrums
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Realtime Simulation of Thin-Shell Deformable Materials using CNN-Based Mesh Embedding
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DenseCAvoid: Real-time Navigation in Dense Crowds using Anticipatory Behaviors
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ENEE408I Squats
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EVDodgeNet: Deep Dynamic Obstacle Dodging with Event Cameras [ICRA 2020]
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Robot navigation in dense crowds
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EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras
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Unsupervised Learning of Dense Optical Flow, Depth and Egomotion from Sparse Event Data [Updated]
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Robotic Imitation
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GapFlyt: Active Vision Based Minimalist Structureless Gap Detection For Quadrotor Flight (IROS 2018)
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microwave demo
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Realtime Pedestrian Behavior Learning for Path Prediction and Navigation
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Compliant Object Cleaning
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Visual processes of action recognition
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UMD robot that learns to cook by watching YouTube video
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UMD robot learns to make a beverage by observing people.
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Robotic Cleaning by Scrubbing
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Bimanual Robotic Cleaning of Compliant Parts
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New Robot Sensing Hand for Co-robotics
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RoboSAM: Robotic Smart Assistant for Manufacturing
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Baxter Robot Learning to Pour into a Moving Container
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Using Failure-to-Success Transitions in an Imitation Learning Framework
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Imitation Learning of Motion Parameters for Dynamic Manipulation Tasks
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Semiautonomous Teleoperation
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Stable with input output delay
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Private video
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Private video
Faculty
John S. BarasDistinguished University Professor301.405.6606 | baras@umd.edu Profile |
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Cornelia FermüllerResearch Scientist301.405.1768 | fermulcm@umd.edu Profile |
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Don PerlisProfessor Emeritus301-405-2685 | perlis@cs.umd.edu Profile |
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James A. ReggiaProfessor Emeritus301-405-2686 | reggia@cs.umd.edu Profile |
Ramani DuraiswamiProfessor(301)405-6710 | ramani@umiacs.umd.edu Profile |
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Dinesh ManochaDistinguished University Professor301.405.2741 | dmanocha@umd.edu Profile |
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Yiannis AloimonosProfessor301.405.1743 | jyaloimo@umd.edu Profile |
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