Han‐Lim Choi

This paper addresses task allocation to coordinate a fleet of autonomous vehicles by presenting two decentralized algorithms: the consensus-based auction algorithm (CBAA) and its generalization to the multi-assignment problem, i.e., the consensus-based bundle algorithm (CBBA). These algorithms utilize a market-based decision strategy as the mechanism for decentralized task selection and use a consensus routine based on local communication as the conflict resolution mechanism to achieve agreement

This paper presents decentralized methods for allocating heterogeneous tasks to a network of agents with different capabilities, when the rules of engagement dictate various cooperation constraints. The new methods are built upon the consensus-based bundle algorithm (CBBA), and the key extensions to the baseline CBBA are: (a) task decomposition and associated scoring modification to allow for soft-constrained cooperation preference, and (b) a decentralized task elimination protocol to ensure sat

This paper addresses anomaly detection and monitoring for swarm drone flights. While the current practice of swarm flight typically relies on the operator’s naked eyes to monitor health of the multiple vehicles, this work proposes a machine learning-based framework to enable detection of abnormal behavior of a large number of flying drones on the fly. The method works in two steps: a sequence of two unsupervised learning procedures reduces the dimensionality of the real flight test data and labe

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2009.

This paper proposes an efficient approach to an observation targeting problem that is complicated by a combinatorial number of targeting choices and the large dimension of the system state, when the goal is to minimize the uncertainty in some quantities of interest. The primary improvements in the efficiency are obtained by computing the impact of each possible measurement choice on the uncertainty reduction backwards. This backward method provides an equivalent solution to a traditional forward

A spacecraft attitude control system provides mechanical and electrical control to achieve the required functions under various mission scenarios. Although generally designed to be highly reliable, mission failure can occur if anomalies occur and the attitude control system fails to properly orient and stabilize the spacecraft. Because accessing spacecraft to directly repair such problems is usually infeasible, developing a continuous condition monitoring model is necessary to detect anomalies a

This paper presents an efficient targeting algorithm to coordinate a team of mobile sensor platforms in order to extract information from the natural environment for the purpose of improved forecasting. This coordinated targeting is complicated by the large dimensionality of the natural dynamic systems (and thus of the decision space), as well as by the constraints in the vehicle motions. While the backward formulation developed by the present authors provides a baseline framework to efficiently

In this paper we studied a system fault detection and isolation in a networked Multi-UAVs formation flight set-up using a Cubature Kalman Filter (CKF). Both actuator and sensor faults of a UAV are considered as an agent node fault on the system of UAVs in the formation flight. The CKF based fault detection scheme developed is used in order to detect a system wide fault in the formation flight. Furthermore, the graph theoretic approach used for modeling the multi agent UAV’s communication is expl

This paper addresses tactical decisions in beyond-visual-range (BVR) air combat between two adversarial teams of multiple (autonomous) aircraft. A BVR combat is formalized as a two-player stochastic game consisting of a sequence of normal-form games that determines on the number of missiles to be allocated to each adversary aircraft; within this normal-form game a continuous sub-game is embedded to determine the missile shooting times. The formulation reduces the size of decision space by taking

This work presents an efficient algorithm for an observation targeting problem that is complicated by the combinatorial number of targeting choices. The approach explicitly incorporates an ensemble forecast to ensure that the measurements are chosen based on their expected improvement in the forecast at a separate verification time and location. The primary improvements in the efficiency are obtained by computing the impact of each possible measurement on the uncertainty reduction over this veri

Application of Unmanned Areal Vehicles for both civilian and military demands improved safety conditions to avoid potential malfunction and accidents in critical mission deployment. This paper presents a method for fault detection and identification (FDI) of actuator fault of a quadrotor. A combination of an Unknown Input Observer (UIO) and Beard Basic Fault Detection Filters (BFDF) are used to generate robust and directional residual using unknown input and eignestructure assignment respectivel