9 papers
Submodular Optimization with Applications to Decision and Control
Shamak Dutta, Bahman Gharesifard, Stephen L. Smith
Submodular set functions, characterized by the diminishing-returns property, provide a unifying combinatorial framework for many subset-selection problems in decision and control.…
Efficient Multi-Objective Planning with Weighted Maximization Using Large Neighbourhood Search
Krishna Kalavadia, Shamak Dutta, Yash Vardhan Pant +1
Autonomous navigation often requires the simultaneous optimization of multiple objectives. The most common approach scalarizes these into a single cost function using a weighted su…
Hierarchical Informative Path Planning via Graph Guidance and Trajectory Optimization
Avraiem Iskandar, Shamak Dutta, Kevin Murrant +2
We study informative path planning (IPP) with travel budgets in cluttered environments, where an agent collects measurements of a latent field modeled as a Gaussian process (GP) to…
A Unified Approach to Optimally Solving Sensor Scheduling and Sensor Selection Problems in Kalman Filtering
Shamak Dutta, Nils Wilde, Stephen L. Smith
We consider a general form of the sensor scheduling problem for state estimation of linear dynamical systems, which involves selecting sensors that minimize the trace of the Kalman…
Approximation Algorithms for Robot Tours in Random Fields with Guaranteed Estimation Accuracy
Shamak Dutta, Nils Wilde, Pratap Tokekar +1
We study the sample placement and shortest tour problem for robots tasked with mapping environmental phenomena modeled as stationary random fields. The objective is to minimize the…
Informative Path Planning in Random Fields via Mixed Integer Programming
Shamak Dutta, Nils Wilde, Stephen L. Smith
We present a new mixed integer formulation for the discrete informative path planning problem in random fields. The objective is to compute a budget constrained path while collecti…
An Improved Greedy Algorithm for Subset Selection in Linear Estimation
Shamak Dutta, Nils Wilde, Stephen L. Smith
In this paper, we consider a subset selection problem in a spatial field where we seek to find a set of k locations whose observations provide the best estimate of the field value…
Convolutional Neural Networks Regularized by Correlated Noise
Shamak Dutta, Bryan Tripp, Graham Taylor
Neurons in the visual cortex are correlated in their variability. The presence of correlation impacts cortical processing because noise cannot be averaged out over many neurons. In…
Barcodes for Medical Image Retrieval Using Autoencoded Radon Transform
Hamid R. Tizhoosh, Christopher Mitcheltree, Shujin Zhu +1
Using content-based binary codes to tag digital images has emerged as a promising retrieval technology. Recently, Radon barcodes (RBCs) have been introduced as a new binary descrip…