37 citations · 57 across the 27 of their papers we have counts for
28 papers
Multi-agent Power Grid Restoration Under Uncertainty Considering Coupled Transportation-Power Networks
Harshal D. Kaushik, Roshni Anna Jacob, Souma Chowdhury +1
Restoring power distribution systems after extreme events such as tornadoes presents significant logistical and computational challenges. The complexity arises from the need to coo…
Distribution Network Restoration: Resource Scheduling Considering Coupled Transportation-Power Networks
Harshal D. Kaushik, Roshni Anna Jacob, Souma Chowdhury +1
Optimal decision-making is key to efficient allocation and scheduling of repair resources (e.g., crews) to service affected nodes of large power grid networks. Traditional manual r…
Fast Decision Support for Air Traffic Management at Urban Air Mobility Vertiports using Graph Learning
Prajit KrisshnaKumar, Jhoel Witter, Steve Paul +3
Urban Air Mobility (UAM) promises a new dimension to decongested, safe, and fast travel in urban and suburban hubs. These UAM aircraft are conceived to operate from small airports…
CONSTRUCT: A Program Synthesis Approach for Reconstructing Control Algorithms from Embedded System Binaries in Cyber-Physical Systems
Ali Shokri, Alexandre Perez, Souma Chowdhury +6
We introduce a novel approach to automatically synthesize a mathematical representation of the control algorithms implemented in industrial cyber-physical systems (CPS), given the…
Physics-Infused Machine Learning Based Prediction of VTOL Aerodynamics with Sparse Datasets
Manaswin Oddiraju, Divyang Amin, Michael Piedmonte +1
Complex optimal design and control processes often require repeated evaluations of expensive objective functions and consist of large design spaces. Data-driven surrogates such as…
Learning Constrained Corner Node Trajectories of a Tether Net System for Space Debris Capture
Feng Liu, Achira Boonrath, Prajit KrisshnaKumar +2
The earth's orbit is becoming increasingly crowded with debris that poses significant safety risks to the operation of existing and new spacecraft and satellites. The active tether…
Efficient Planning of Multi-Robot Collective Transport using Graph Reinforcement Learning with Higher Order Topological Abstraction
Steve Paul, Wenyuan Li, Brian Smyth +3
Efficient multi-robot task allocation (MRTA) is fundamental to various time-sensitive applications such as disaster response, warehouse operations, and construction. This paper tac…
Graph Learning Based Decision Support for Multi-Aircraft Take-Off and Landing at Urban Air Mobility Vertiports
Prajit KrisshnaKumar, Jhoel Witter, Steve Paul +2
Majority of aircraft under the Urban Air Mobility (UAM) concept are expected to be of the electric vertical takeoff and landing (eVTOL) vehicle type, which will operate out of vert…
Conceptual Design of Cellular Auxetic Systems with Passive Adaptation to Loading
Joshua Prendergast, Manaswin Oddiraju, Mostafa Nouh +1
Auxetics refer to a class of engineered structures which exhibit an overall negative Poisson's ratio. These structures open up various potential opportunities in impact resistance,…
Efficient Concurrent Design of the Morphology of Unmanned Aerial Systems and their Collective-Search Behavior
Chen Zeng, Prajit KrisshnaKumar, Jhoel Witter +1
The collective operation of robots, such as unmanned aerial vehicles (UAVs) operating as a team or swarm, is affected by their individual capabilities, which in turn is dependent o…
Learning Scalable Policies over Graphs for Multi-Robot Task Allocation using Capsule Attention Networks
Steve Paul, Payam Ghassemi, Souma Chowdhury
This paper presents a novel graph reinforcement learning (RL) architecture to solve multi-robot task allocation (MRTA) problems that involve tasks with deadlines and workload, and…
Efficient Training of Transfer Mapping in Physics-Infused Machine Learning Models of UAV Acoustic Field
Rayhaan Iqbal, Amir Behjat, Revant Adlakha +3
Physics-Infused Machine Learning (PIML) architectures aim at integrating machine learning with computationally-efficient, low-fidelity (partial) physics models, leading to improved…
Learning Robust Policies for Generalized Debris Capture with an Automated Tether-Net System
Chen Zeng, Grant Hecht, Prajit KrisshnaKumar +3
Tether-net launched from a chaser spacecraft provides a promising method to capture and dispose of large space debris in orbit. This tether-net system is subject to several sources…
Using Physiological Information to Classify Task Difficulty in Human-Swarm Interaction
Joseph P. Distefano, Hemanth Manjunatha, Souma Chowdhury +3
Human-swarm interaction has recently gained attention due to its plethora of new applications in disaster relief, surveillance, rescue, and exploration. However, if the task diffic…
Learning Robot Swarm Tactics over Complex Adversarial Environments
Amir Behjat, Hemanth Manjunatha, Prajit KrisshnaKumar +8
To accomplish complex swarm robotic missions in the real world, one needs to plan and execute a combination of single robot behaviors, group primitives such as task allocation, pat…
Efficient Inverse Design of 2D Elastic Metamaterial Systems Using Invertible Neural Networks
Manaswin Oddiraju, Amir Behjat, Mostafa Nouh +1
Locally resonant elastic metamaterials (LREM) can be designed, by optimizing the geometry of the constituent self-repeating unit cells, to potentially damp out vibration in selecte…
Scalable Coverage Path Planning of Multi-Robot Teams for Monitoring Non-Convex Areas
Leighton Collins, Payam Ghassemi, Ehsan T. Esfahani +3
This paper presents a novel multi-robot coverage path planning (CPP) algorithm - aka SCoPP - that provides a time-efficient solution, with workload balanced plans for each robot in…
Deep Learning based Multi-Modal Sensing for Tracking and State Extraction of Small Quadcopters
Zhibo Zhang, Chen Zeng, Maulikkumar Dhameliya +2
This paper proposes a multi-sensor based approach to detect, track, and localize a quadcopter unmanned aerial vehicle (UAV). Specifically, a pipeline is developed to process monocu…
Metamodel Based Forward and Inverse Design for Passive Vibration Suppression
Amir Behjat, Manaswin Oddiraju, Mohammad Ali Attarzadeh +2
Aperiodic metamaterials represent a class of structural systems that are composed of different building blocks (cells), instead of a self-repeating chain of the same unit cells. Op…
Hybrid modeling: Applications in real-time diagnosis
Ion Matei, Johan de Kleer, Alexander Feldman +2
Reduced-order models that accurately abstract high fidelity models and enable faster simulation is vital for real-time, model-based diagnosis applications. In this paper, we outlin…
Informative Path Planning with Local Penalization for Decentralized and Asynchronous Swarm Robotic Search
Payam Ghassemi, Souma Chowdhury
Decentralized swarm robotic solutions to searching for targets that emit a spatially varying signal promise task parallelism, time efficiency, and fault tolerance. It is, however,…
Decentralized Dynamic Task Allocation in Swarm Robotic Systems for Disaster Response
Payam Ghassemi, David DePauw, Souma Chowdhury
Multiple robotic systems, working together, can provide important solutions to different real-world applications (e.g., disaster response), among which task allocation problems fea…
Adaptive Model Refinement with Batch Bayesian Sampling for Optimization of Bio-inspired Flow Tailoring
Payam Ghassemi, Sumeet Sanjay Lulekar, Souma Chowdhury
This paper presents an advancement to an approach for model-independent surrogate-based optimization with adaptive batch sampling, known as Adaptive Model Refinement (AMR). While t…
Training Detection-Range-Frugal Cooperative Collision Avoidance Models for Quadcopters via Neuroevolution
Amir Behjat, Krushang Gabani, Souma Chowdhury
Cooperative autonomous approaches to avoiding collisions among small Unmanned Aerial Vehicles (UAVs) is central to safe integration of UAVs within the civilian airspace. One potent…