Aerospace Controls Laboratory

Welcome to ACL

We research topics related to autonomous systems and control design for aircraft, spacecraft, and ground vehicles. Theoretical research is pursued in areas such as:

  • Decision making under uncertainty
  • Path planning, activity, and task assignment
  • Estimation and navigation
  • Robust control, adaptive control, and model predictive control
  • Machine learning and reinforcement learning methods

Recent News

5 Papers Accepted to ICRA 2019

ACL co-authored 5 papers accepted to ICRA 2019! Congratulations to all authors.

Papers

ACL paper about Learning to Teach won AAAI-19 Outstanding Student Paper Honorable Mention!

Congrats to Shayegan Omidshafiei, Dong Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Chris Amato, Murray Campbell for their paper Learning to Teach in Cooperative Multiagent Reinforcement Learning! They are looking forward to present and discuss the work at AAAI-19 this end of January.

Fleets of drones could aid searches for lost hikers - MIT News

System allows drones to cooperatively explore terrain under thick forest canopies where GPS signals are unreliable.

MIT News Article

ACL at IROS 2018

ACL members (Björn Lütjens, Kris Frey, Macheng Shen, Michael Everett) have published works at IROS 2018!

Papers

Shayegan has graduated from ACL!

Congratulations to Shayegan Omidshafiei who has finished his PhD in Decentralized Teaching and Learning in Cooperative Multiagent Systems at ACL. Thanks for all the helpful advice to the first-years and best of all luck researching Google DeepMind in Paris!

Shayegan’s Homepage, Shayegan’s Thesis

ACL finalist for ICRA Best Multi-Robot Systems Paper Award 2018!

ACL paper Talk Resource-Efficiently to Me: Optimal Communication Planning for Distributed Loop Closure Detection by Matthew Giamou, Kasra Khosoussi and Jonathan P. How was a finalist for the ICRA Best Multi-Robot Systems Paper Award 2018.

Awards page, Nominated paper