DAS Lab

What if hundreds of robots and drones worked together to optimize your farm?
What if excavators and backhoes learned from the best operators and taught you new tricks?
What if thousands of drones and robots collaborated to reveal denied and concealed information?

These and other visions for a better tomorrow drive our research at the Distributed Autonomous Systems (DAS) Laboratory. We pursue research at the intersection of decision and control theory, machine learning, and robotics. Our goal is to enable the next generation of autonomous systems that operate reliably in stochastic time-varying and distributed settings. We are a highly motivated and dedicated group of interdisciplinary researchers focused on challenging the state of the art.

You can visit us in AESB 128 on the University of Illinois Urbana-Champaign campus.

We are an interdisciplinary lab affiliated with multiple departments across he UIUC campus: Agricultural and Biological Engineering , Coordinated Science Lab , Aerospace Engineering, and the Beckman Institute

Prospective Students: We are a highly interdisciplinary robotics and control lab. We welcome top students from all disciplines of engineering and computer science to apply.


Director:
A. Prof. Girish Chowdhary

Dynamic Data Driven Pervasive Situational Awareness (DDDPSA)

We are developing new adaptive planning techniques for pervasive battle-space situational awareness with ground and aerial sensors. This project is funded by AFOSR's DDDAS program.

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AFOSR YIP: Robust Adaptive Autonomy in Contested Environments (RAACE)

We are developing new spatiotemporally scalable learning, planning, and manned-unmanned collaboration algorithms for teams of UAS operating in consented environments. This project is funded by AFOSR Young Investigator Program (YIP).

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Surface and airborne sensors for detecting CO2 leakage

Our role in the CO2-Enhanced Oil Recovery Pilot in the Anadarko Basin (TX) is develop CO2 flux monitoring technologies using UAS and ground sensors. This project is funded by US Department of Energy (DOE).

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Multi-Objective Optimization for Flexible Transport Aircraft

We created online adaptive multi-objective optimization based active wing-shaping controllers for next generation light-weight and flexible aircraft. This project is funded by NASA, and OK-Space Grant consortium.

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DASLAB Experimental Infrastructures

We have developed state-of-the-art facilities and infrastructure to support cutting edge autonomy research.

Novel Data-Driven Algorithms and Software.

  • Algorithms for Spatiotemporal Agricultural Data Modeling

  • Algorithms and software for Bayesian Nonparametric Learning

  • Familiarity Based Navigation Algorithms

  • Planning and Reinforcement Learning Algorithms in Dynamic time-varying Environments

  • Learning from Demonstration and Input Segmentation Algorithms

Unmanned Aerial Vehicles

  • Muggin: 10 ft wingspan fixed-wing UAS

  • Penguin-B: 11 ft wingspan fixed-wing UAS

  • Skyhunter: 6 ft wingspan fixed-wing UAS

  • Quadrotor Platforms

Experimental Facilities

  • OptiTrac Motion Capture System

  • UAFS Unmanned Aircraft Flight Sation

  • Hardware-in-the-Loop Flight Simulation

  • Cloud based Multi Agent Game Emulator (MAGE)

Unmanned Surface Vehicles

  • Caterpillar 1-14 Scale Excavator Model

  • Europa Bot

  • OSU Autonomous Golf Cart Project

  • TurtleBot

Stabilis Autopilot

  • Stabilis Onboard Autonomy Module (Autopilot)