Autonomous Systems
Micro air vehicles; uncrewed sea surface vehicles; uncrewed underwater vehicles; and planetary surface rovers; and robot motion planning.
Stories / March 8, 2023
The Falcon and the Flock
Stories / February 24, 2023
UMD’s SeaDroneSim can generate simulated images and videos to...
Stories / January 19, 2023
New algorithms for multi-robot systems in low communication...
Stories / January 5, 2023
ArtIAMAS receives third-year funding of up to $15.1M
Stories / January 5, 2023
Work on the future of regulating autonomous systems published...
Stories / December 8, 2022
Autonomous drones based on bees use AI to work together
Stories / November 16, 2022
SoCal Edison Taps UAS Service Provider for Inspections
Stories / October 25, 2022
Navy Demos Wide Range Of VTOL Systems For Future Operations
Stories / October 20, 2022
Test Site Becomes UMD UAS Research and Operations Center
Stories / October 19, 2022
The Modern Battle for Maryland’s Oysters
Videos
Autonomous Systems
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Autonomous Bartender Robot in a Crowd -
EVPropNet: Detecting Drones By Finding Propellers For Mid-Air Landing and Following -
ENPM 808 independent study: Locomotion of quadruped over uneven terrain -
MorphEyes: Variable Baseline Stereo For Quadrotor Navigation -
0-MMS: Zero-Shot Multi-Motion Segmentation With A Monocular Event Camera -
Autonomous Social Distancing in Urban Environments using a Quadruped Robot -
COVID-Robot: Monitoring Social Distancing Constraints in Crowded Scenarios -
Crowd-Steer: Smooth and Collision-Free Navigation in Dense Scenarios Using High-Fidelity Simulation -
Developing Robots to Collect Scientific Data -
VFS MAV Student Challenge - Gate 2 Autonomous Entry -
UMD AMAV 2020 Gate 2 Video -
IROS 2019 Autonomous Drone Racing, University of Maryland dry run -
GraphRQI: Classifying Driver Behaviors Using Graph Spectrums -
DeepMNavigate: Deep Reinforced Multi-Robot Navigation Unifying Local & Global Collision Avoidance -
DenseCAvoid: Real-time Navigation in Dense Crowds using Anticipatory Behaviors -
CDCL Cooperative Mapping and Target Search -
EVDodgeNet: Deep Dynamic Obstacle Dodging with Event Cameras [ICRA 2020] -
EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras -
Unsupervised Learning of Dense Optical Flow, Depth and Egomotion from Sparse Event Data [Updated] -
Inspired by nature -
Research into Remote Control of Semiautonomous Cars -
GapFlyt: Active Vision Based Minimalist Structureless Gap Detection For Quadrotor Flight (IROS 2018) -
CDCL Quadrotor Swarming and Pursuit -
Realtime Pedestrian Behavior Learning for Path Prediction and Navigation -
CDCL Quadrotor Swarm -
Robo Terp 3 -
Ocean Sampling with Autonomous Vehicles: Frank Lagor -
ARC Lab quadcopter demonstrations -
Topological Velocity Alignment (TVA) -
Beacon-referenced cyclic pursuit (cbCPb)—Three agents -
Beacon-referenced cyclic pursuit (cbCPb)—Five agents -
Robo Raven: RC Car Assisted Takeoff -
The UMD Space Systems Laboratory: RASC-AL 2012 Robo-Ops Competition Outreach Video -
Adaptive Sampling Based COLREGs-Compliant Target Following for Autonomous Surface Vehicles -
RoboTerp II: Improved Design Inspired by Diamondback Terrapin -
R2G2: Camouflaging, pipe-inspection, and high traction capabilities -
Robo Raven IV: Autonomy (UMD Robotics) -
Model-Predictive Asset Defense by Team of Autonomous Surface Vehicles -
Model-Predictive Target Defense by Team of Unmanned Surface Vehicles -
Dynamics-Aware Target Following for USV Operating under COLREGS in Civilian Traffic -
Real-time Dynamics Simulation of Unmanned Sea Surface Vehicle for Virtual Environments -
Learning from Demonstration to Learn Waypoint Approach in the Presence of Active Blockers -
Automated Synthesis of Action Selection Policies for USVs Operating in Adverse Environments -
Trajectory Planning for Unmanned Surface Vehicles (USVs) to Handle Sea Disturbances -
Target Following for Unmanned Surface Vehicle (USV) Operating in Cluttered Environments -
Turn Around Behavior Generation and Execution for Unmanned Ground Vehicles -
Follow Behavior for Unmanned Surface Vehicle -
Follow Behavior for Unmanned Ground Vehicle -
Amphibious Crocodile Platform: Walking and Swimming -
Track-Following Robot
Faculty
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David AkinProfessor301-405-1138 | dakin@ssl.umd.edu Profile |
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Bilal M. AyyubProfessor301-405-1956 | ba@umd.edu Profile |
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Gil BlankenshipProfessor and Associate Chair for External Affairs(301)405-3632 | gilmer@umd.edu Profile |
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Nikhil ChopraProfessor301.405.7011 | nchopra@umd.edu Profile |
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Michael OtteAssistant Professor301-405-2723 | otte@umd.edu Profile |
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Abhinav ShrivastavaAssistant Professor301-405-7952 | abhinav2@umd.edu Profile |
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Eleonora TubaldiAssistant Professor(301) 405 5272 | etubaldi@umd.edu Profile |
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Yiannis AloimonosProfessor301.405.1743 | jyaloimo@umd.edu Profile |
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John S. BarasDistinguished University Professor301.405.6606 | baras@umd.edu Profile |
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Hugh BruckProfessor301-405-8711 | bruck@umd.edu Profile |
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Dinesh ManochaDistinguished University Professor301.405.2741 | dmanocha@umd.edu Profile |
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Derek A. PaleyWillis H. Young Jr. Professor of Aerospace Engineering Education301-405-5757 | dpaley@umd.edu Profile |
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Pratap TokekarAssociate Professor| tokekar@umd.edu Profile |
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