10 papers
Finite-Sample Conformal Coverage Recovery via Fusion under Degraded Local Guarantees in Occupancy Map Estimation
Ritvik Mahajan, Aneesh Raghavan, Karl Henrik Johansson
Accurate and reliable environmental mapping is a fundamental requirement for multi-robot autonomy. While continuous mapping techniques like Gaussian Process Occupancy Mapping (GPOM…
Approximate Simulation-Based Verification of Compatibility of the Friedkin-Johnsen Model with Binary Observations
Yu Xing, Aneesh Raghavan, Michael T. Schaub +1
We consider a verification problem for opinion dynamics based on binary observations. The opinion dynamics is governed by a Friedkin-Johnsen (FJ) model, where only a sequence of bi…
Sequential Binary Hypothesis Testing with Competing Agents under Information Asymmetry
Aneesh Raghavan, M. Umar B. Niazi, Karl H. Johansson
This paper concerns sequential hypothesis testing in competitive multi-agent systems where agents exchange potentially manipulated information. Specifically, a two-agent scenario i…
An Active Parameter Learning Approach to The Identification of Safe Regions
Aneesh Raghavan, Karl H Johansson
We consider the problem of identification of safe regions in the environment of an autonomous system. The environment is divided into a finite collections of Voronoi cells, with ea…
Collaborative Estimation of Real Valued Function by Two Agents and a Fusion Center with Knowledge Exchange
Aneesh Raghavan, Karl H. Johansson
We consider a collaborative iterative algorithm with two agents and a fusion center for estimation of a real valued function (or ``model") on the set of real numbers. While the dat…
Motion Planning for Identification of Linear Classifiers
Aneesh Raghavan, Karl Henrik Johansson
A given region in 2-D Euclidean space is divided by a unknown linear classifier in to two sets each carrying a label. The objective of an agent with known dynamics traversing the r…
Distributed Estimation by Two Agents with Different Feature Spaces
Aneesh Raghavan, Karl Henrik Johansson
We consider the problem of estimation of a function by a system consisting of two agents and a fusion center. The two agents collect data comprising of samples of an independent va…
Distributed Learning and Function Fusion in Reproducing Kernel Hilbert Space
Aneesh Raghavan, Karl Henrik Johansson
We consider the problem of function estimation by a multi-agent system comprising of two agents and a fusion center. Each agent receives data comprising of samples of an independen…
Order Effects of Measurements in Multi-Agent Hypothesis Testing
Aneesh Raghavan, John S. Baras
In multi-agent systems, agents observe data, and use them to make inferences and take actions. As a result sensing and control naturally interfere, more so from a real-time perspec…
Cooperative Hypothesis Testing by Two Observers with Asymmetric Information
Aneesh Raghavan, John S. Baras
We consider the binary hypothesis testing problem with two observers. There are two possible states of nature (or hypotheses). Observations collected by the two observers are stati…