Current and Recent Projects

Automated Battery Management System for Enabling Multi-Agent Persistent Missions by Tuna Toksoz, N. Kemal Ure, and Josh Redding

Consensus-Based Bundle Algorithm (CBBA) by Luke Johnson, Sameera Ponda, and Han-Lim Choi

Gradient Projection Anti-windup Scheme by Justin Teo

Information-rich Path Planning for Constrained Mobile Sensor Networks by Dan Levine and Brandon Luders

Multi-Vehicle Health Management by Josh Redding and Brett Bethke

Parameter Estimation and Control of UAV by Frank Fan

Reward Learning from Demonstration by Buddy Michini

Robust Planning and Control for Agile Robotics for Logistics by Brandon Luders and Vishnu Desaraju

Scaling Reinforcement Learning Methods by Incremental Feature Dependency Discovery by Alborz Geramifard

Threat Assessment Design for Driver Assistance System at Intersections by Georges Aoude, Brandon Luders, et al.

UAVs helping a human supervisor map an area that has just experienced a Chemical / Biological / Radiological / Nuclear (CBRN) incident by Aditya Undurti

Variable-Pitch Quadrotor by Mark Cutler

Former Projects

• Autonomous Air Combat by Jim McGrew


• Closed-Loop Control of Autonomous Spacecraft by Matt Jeffrey


• [+] Control of Autonomous Formation Flying Spacecraft by Louis Breger
  [−] Control of Autonomous Formation Flying Spacecraft by Louis Breger
  There are many challenges associated with flying multiple satellites in formation. This work examines approaches for initializing, coordinating, and controlling spacecraft formations in the presence of process noise and navigation error.


• Coordinated Control of Multiple Mobile Observing Platforms for Weather Forecast Improvement by Han-Lim Choi


• Coordinated Search and Track (CSAT) by Karl Kulling and Luc Brunet


• Decentralized Exploration under Communication Constraints by Emily Craparo


• Environment Mapping using Computer Vision by Ray He


• Flight Experiments Using Mixed-Integer Linear Programming (MILP) Trajectory Optimization by Kieran Culligan, Brandon Luders, Yoshiaki Kuwata, and Mario Valenti


• Kernel-Based Approximate Dynamic Programming by Brett Bethke


• [+] Mixed-integer Linear Programming (MILP) Trajectory Design Algorithms by Arthur Richards
  [−] Mixed-integer Linear Programming (MILP) Trajectory Design Algorithms by Arthur Richards
  MILP trajectory design algorithms were successfully flight tested by Boeing using two vehicles (F-15E/ T-33) under DARPAs Software Enabled Control program (Summer 2004). The overall approach has also been demonstrated in real-time using ACL's eight rover testbed and during numerous flights of ACL's multi-UAV testbed.


• Nonlinear Controller on a Fixed Wing Aircraft by Frant Sobolic and Saif Al-Hiddabi


• Onboard Planning System for UAVs in Support of Expeditionary Reconnaissance and Surveillance (OPS-USERS) by Cam Fraser


• [+] Orion Formation Flying Mission
  [−] Orion Formation Flying Mission
  This mission is being designed and built by MIT and Stanford. In August 2001, a paper was presented at the AIAA Space 2001 Conference and Exposition in Albuquerque, New Mexico. The paper addressed the status of the project at the time and performed an analysis of mission operations.


• Path Planning for Multiple Spacecraft Reconfiguration Maneuvers and Application to SPHERES onboard ISS by Georges Aoude


• Planning and Control for the Darpa Urban Challenge by Yoshi Kuwata, Chun Sang Teo and Gaston Fiore


• [+] Rapid Planning Algorithms for Cooperating Multi-Vehicle Teams by Mehdi Alighanbari
  [−] Rapid Planning Algorithms for Cooperating Multi-Vehicle Teams by Mehdi Alighanbari
  The goal is to develop a general methodology for the team tasking and cooperative path planning components of hierarchical coordination architecture for teams of UAV's.


• [+] Receding Horizon Control of Autonomous Aerial Vehicles by John Bellingham and Yoshi Kuwata
  [−] Receding Horizon Control of Autonomous Aerial Vehicles by John Bellingham and Yoshi Kuwata
  This work presents a new approach to trajectory optimization for autonomous aerial vehicles performing large-scale maneuvers. We have developed a receding horizon trajectory planner based on Mixed Integer-Linear Programming (MILP) that is capable of planning planar trajectories to a goal. The planner can handle constraints such as no-fly areas and aircraft dynamics.


• Robust Decision-Making Problems by Luca Bertuccelli


• Vision Aided Navigation in Unknown Environments by Spencer Ahrens and Dan Levine