
Mu, Beipeng; How, Jonathan
For the problem of learning sparse Gaussian graphical models, it is desirable to obtain both sparse structures as well as good parameter estimates. Classical techniques, such as optimizing the l1regularized maximum likelihood or ChowLiu algorithm, either focus on parameter estimation or constrain to speci c structure. This paper proposes an alternative that is based on l0regularized maximum likelihood and employs a greedy algorithm to solve the optimization problem. We show that, when the graph is acyclic, the greedy solution finds the optimal acyclic graph. We also show it can update the parameters in constant time when connecting two subcomponents, thus...

Chowdhary, Girish; Kingravi, Hassan A.; How, Jonathan P.; Vela, Patricio A.
Realworld dynamical variations make adaptive control of timevarying systems highly relevant. However, most adaptive control literature focuses on analyzing systems where the uncertainty is represented as a weighted linear combination of fixed number of basis functions, with constant weights. One approach to modeling time variations is to assume time varying ideal weights, and use difference integration to accommodate weight variation. However, this approach reactively suppresses the uncertainty, and has little ability to predict system behavior locally. We present an alternate formulation by leveraging Bayesian nonparametric Gaussian Process adaptive elements. We show that almost surely bounded adaptive controllers for a class...

Chowdhary, Girish; Kingravi, Hassan A.; How, Jonathan P.; Vela, Patricio A.
Most current Model Reference Adaptive Control
(MRAC) methods rely on parametric adaptive elements, in
which the number of parameters of the adaptive element are
fixed a priori, often through expert judgment. An example of
such an adaptive element are Radial Basis Function Networks
(RBFNs), with RBF centers preallocated based on the expected
operating domain. If the system operates outside of the expected
operating domain, this adaptive element can become
noneffective in capturing and canceling the uncertainty, thus
rendering the adaptive controller only semiglobal in nature.
This paper investigates a Gaussian Process (GP) based Bayesian
MRAC architecture (GPMRAC), which leverages the power and
flexibility of GP Bayesian nonparametric models of uncertainty.
GPMRAC does not...

Mu, Beipeng; Chowdhary, Girish; How, Jonathan P.
In many distributed sensing applications it is likely that only a few agents will have valuable information at any given time. Since
wireless communication between agents is resourceintensive, it is important to ensure that the communication effort is focused on
communicating valuable information from informative agents. This paper presents communication efficient distributed sensing algorithms
that avoid network cluttering by having only agents with high Value of Information (VoI) broadcast their measurements to the network,
while others censor themselves. A novel contribution of the presented distributed estimation algorithm is the use of an adaptively adjusted
VoI threshold to determine which agents are informative. This adaptation enables...

Mu, Beipeng; How, Jonathan P.; Chowdhary, Girish
In many distributed sensing applications, not all agents have valuable information
at all times. Therefore, requiring all agents to communicate at all times can be
resource intensive. In this work, the notion of Value of Information (VoI) is used to
improve the efficiency of distributed sensing algorithms. Particularly, only agents
with high VoI broadcast their measurements to the network, while others censor
their measurements. New VoI realized data fusion algorithms are introduced, and
an in depth analysis of the costs incurred by these algorithms and conventional
distributed data fusion algorithms is presented. Numerical simulations are used
to compare the performance of the VoI realized algorithms with traditional data
fusion...

Aoude, Georges S.; Luders, Brandon D.; Lee, Kenneth K. H.; Levine, Daniel S.; How, Jonathan P.

Luders, Brandon D.; Aoude, Georges S.; Joseph, Joshua M.; Roy, Nicholas; How, Jonathan P.
This paper presents a realtime path planning algorithm which can guarantee
probabilistic feasibility for autonomous robots subject to process noise and an
uncertain environment, including dynamic obstacles with uncertain motion
patterns. The key contribution of the work is the
integration of a novel method for modeling dynamic obstacles with uncertain future
trajectories. The method, denoted as RRGP, uses a learned motion pattern model
of the dynamic obstacles to make longterm predictions of their future paths. This is done by combining the
flexibility of Gaussian processes (GP) with the efficiency of RRTReach,
a samplingbased reachability computation method which ensures dynamic
feasibility. This prediction model is then utilized within chanceconstrained rapidlyexploring...

Aoude, Georges S.; Luders, Brandon D.; Levine, Daniel S.; How, Jonathan P.
This paper considers the path planning problem for an autonomous vehicle in an
urban environment populated with static obstacles and moving vehicles with
uncertain intents. We propose a novel threat assessment module, consisting of an
intention predictor and a threat assessor, which augments the host vehicle's
path planner with a realtime threat value representing the risks posed by the
estimated intentions of other vehicles. This new threataware planning approach
is applied to the CLRRT path planning framework, used by the MIT team in the
2007 DARPA Grand Challenge. The strengths of this approach are demonstrated
through simulation and experiments performed in the RAVEN testbed facilities.

Teo, Justin; How, Jonathan P.
In a conference paper titled "Geometric Properties of Gradient Projection Antiwindup Compensated Systems," two main results were presented. The first is the controller stateoutput consistency property of gradient projection antiwindup (GPAW) compensated controllers. The second is a geometric bounding condition relating the vector fields of the uncompensated and GPAW compensated closedloop systems with respect to a star domain. While the controller stateoutput consistency property stands without modifications, the proof of the geometric bounding condition depends on two lemmas, the proofs of which were found to be faulty. In this report, we present a new proof of the geometric bounding condition...

Teo, Justin; How, Jonathan P.
The gradient projection antiwindup (GPAW) scheme was recently proposed as an antiwindup method for nonlinear multiinputmultioutput systems/controllers, the solution of which was recognized as a largely open problem in a recent survey paper. This report analyzes the properties of the GPAW scheme applied to an input constrained first order linear time invariant (LTI) system driven by a first order LTI controller, where the objective is to regulate the system state about the origin. We show that the GPAW compensated system is in fact a projected dynamical system (PDS), and use results in the PDS literature to assert existence and uniqueness...

Aoude, Georges S.; How, Jonathan P.
Classifying other agents’ intentions is a very complex task but it can be very essential in assisting (autonomous or human) agents in navigating safely in dynamic and possibly hostile environments. This paper introduces a classification approach based on support vector machines and Bayesian filtering (SVMBF). It then applies it to a road intersection problem to assist a vehicle in detecting the intention of an approaching suspicious vehicle. The SVMBF approach achieved very promising results.

Teo, Justin; How, Jonathan P.
Approximate Dynamic Inversion has been established as a method to control minimumphase, nonaffineincontrol systems [1]. In this report, we restate the main results of [1], clarify some minor notational errors, and prove the same results in an expanded form. In the large, the main results of [1] still stand. The development follows [1] closely, and no novelty is claimed herein. The purpose of this report is mainly to supplement our existing results in [2]–[4] that rely heavily on the results of [1].

Bertuccelli, Luca F.; How, Jonathan P.
This paper discusses the problem of a distributed network of agents attempting to agree on an imprecise probability over a network. Unique from other related work however, the agents must reach agreement while accounting for relative uncertainties in their respective probabilities. First, we assume that the agents only seek to agree to a centralized estimate of the probabilities, without accounting for observed transitions. We provide two methods by which such an agreement can occur which uses ideas from Dirichlet distributions. The first methods interprets the consensus problem as an aggregation of Dirichlet distributions of the neighboring agents. The second method...

Teo, Justin; How, Jonathan P.
Approximate Dynamic Inversion (ADI) has been established as a method to control minimumphase, nonaffineincontrol systems. Previous results have shown that for singleinput nonaffineincontrol systems, every ADI controller admits a linear ProportionalIntegral (PI) realization that is largely independent of the nonlinear function that defines the system. In this report, we first present an extension of the ADI method for singleinput nonaffineincontrol systems that renders the closedloop error dynamics independent of the reference model dynamics. The equivalent PI controller will be derived and both of these results are then extended to multiinput nonaffineincontrol systems.

Frank, Adrian; McGrew, James; Valenti, Mario; Levine, Daniel; How, Jonathan P.
This paper presents vehicle models and test flight results for an autonomous fixedwing airplane that is designed to takeoff, hover, transition to and from levelflight modes, and perch on a vertical landing platform in a highly space constrained environment. By enabling a fixedwing UAV to achieve these feats, the speed and range of a fixedwing aircraft in level flight are complimented by hover capabilities that were typically limited to rotorcraft. Flight and perch landing results are presented. This capability significantly eases support and maintenance of the vehicle. All of the flights presented in this paper are performed using the MIT...