M. Ani Hsieh
YOU?
Author Swipe
View article: Accelerating the CLEAN algorithm of radio interferometry with convex optimization
Accelerating the CLEAN algorithm of radio interferometry with convex optimization Open
In radio-interferometry, we recover an image from an incompletely sampled Fourier data. The de-facto standard algorithm, the Cotton-Schwab CLEAN, is iteratively switching between computing a deconvolution (minor loop) and subtracting the m…
View article: Coupled jet coordination and physical arrangement in salp-inspired multi-robot swimming
Coupled jet coordination and physical arrangement in salp-inspired multi-robot swimming Open
Salps are underwater invertebrates considered to be among the world’s most energy-efficient examples of jet propulsion. They can swim as solitary individuals or as physically connected colonies, coordinating their jets to produce collectiv…
View article: Multi-robot Multi-source Localization in Complex Flows with Physics-Preserving Environment Models
Multi-robot Multi-source Localization in Complex Flows with Physics-Preserving Environment Models Open
Source localization in a complex flow poses a significant challenge for multi-robot teams tasked with localizing the source of chemical leaks or tracking the dispersion of an oil spill. The flow dynamics can be time-varying and chaotic, re…
View article: Physics-informed sensor coverage through structure preserving machine learning
Physics-informed sensor coverage through structure preserving machine learning Open
We present a machine learning framework for adaptive source localization in which agents use a structure-preserving digital twin of a coupled hydrodynamic-transport system for real-time trajectory planning and data assimilation. The twin i…
View article: Sequence Modeling for Time-Optimal Quadrotor Trajectory Optimization with Sampling-based Robustness Analysis
Sequence Modeling for Time-Optimal Quadrotor Trajectory Optimization with Sampling-based Robustness Analysis Open
Time-optimal trajectories drive quadrotors to their dynamic limits, but computing such trajectories involves solving non-convex problems via iterative nonlinear optimization, making them prohibitively costly for real-time applications. In …
View article: Probabilistic Multi-Robot Planning with Temporal Tasks and Communication Constraints
Probabilistic Multi-Robot Planning with Temporal Tasks and Communication Constraints Open
Multi-robot systems are broadly used in applications such as search and rescue, environmental monitoring, and mapping of unknown environments. Effective coordination among these robots often relies on distributed information and local deci…
View article: Air-Ground Collaboration for Language-Specified Missions in Unknown Environments
Air-Ground Collaboration for Language-Specified Missions in Unknown Environments Open
As autonomous robotic systems become increasingly mature, users will want to specify missions at the level of intent rather than in low-level detail. Language is an expressive and intuitive medium for such mission specification. However, r…
View article: Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities
Deploying Foundation Model-Enabled Air and Ground Robots in the Field: Challenges and Opportunities Open
The integration of foundation models (FMs) into robotics has enabled robots to understand natural language and reason about the semantics in their environments. However, existing FM-enabled robots primary operate in closed-world settings, …
View article: Climate Extremes at the City–River Interface: Insights from the Philadelphia-Schuylkill System
Climate Extremes at the City–River Interface: Insights from the Philadelphia-Schuylkill System Open
Hurricane Ida struck the U.S. East Coast in August 2021, pushing the Schuylkill River in Philadelphia to a record discharge nearly 100 times larger than its average flow. As one of the most severe disasters of the 21st century, Ida exempli…
View article: RAD-Bench: Evaluating Large Language Models’ Capabilities in Retrieval Augmented Dialogues
RAD-Bench: Evaluating Large Language Models’ Capabilities in Retrieval Augmented Dialogues Open
View article: EnKode: Active Learning of Unknown Flows with Koopman Operators
EnKode: Active Learning of Unknown Flows with Koopman Operators Open
In this letter, we address the task of adaptive sampling to model vector fields. When modeling environmental phenomena with a robot, gathering high resolution information can be resource intensive. Actively gathering data and modeling flow…
View article: Flying Quadrotors in Tight Formations using Learning-based Model Predictive Control
Flying Quadrotors in Tight Formations using Learning-based Model Predictive Control Open
Flying quadrotors in tight formations is a challenging problem. It is known that in the near-field airflow of a quadrotor, the aerodynamic effects induced by the propellers are complex and difficult to characterize. Although machine learni…
View article: Collision-free time-optimal path parameterization for multi-robot teams
Collision-free time-optimal path parameterization for multi-robot teams Open
Coordinating the motion of multiple robots in cluttered environments remains a computationally challenging task. We study the problem of minimizing the execution time of a set of geometric paths by a team of robots with state-dependent act…
View article: RAD-Bench: Evaluating Large Language Models Capabilities in Retrieval Augmented Dialogues
RAD-Bench: Evaluating Large Language Models Capabilities in Retrieval Augmented Dialogues Open
In real-world applications with Large Language Models (LLMs), external retrieval mechanisms - such as Search-Augmented Generation (SAG), tool utilization, and Retrieval-Augmented Generation (RAG) - are often employed to enhance the quality…
View article: Knowledge-based Neural Ordinary Differential Equations for Cosserat Rod-based Soft Robots
Knowledge-based Neural Ordinary Differential Equations for Cosserat Rod-based Soft Robots Open
Soft robots have many advantages over rigid robots thanks to their compliant and passive nature. However, it is generally challenging to model the dynamics of soft robots due to their high spatial dimensionality, making it difficult to use…
View article: Challenges and Opportunities for Large-Scale Exploration with Air-Ground Teams using Semantics
Challenges and Opportunities for Large-Scale Exploration with Air-Ground Teams using Semantics Open
One common and desirable application of robots is exploring potentially hazardous and unstructured environments. Air-ground collaboration offers a synergistic approach to addressing such exploration challenges. In this paper, we demonstrat…
View article: Inferring bifurcation diagrams with transformers
Inferring bifurcation diagrams with transformers Open
The construction of bifurcation diagrams is an essential component of understanding nonlinear dynamical systems. The task can be challenging when one knows the equations of the dynamical system and becomes much more difficult if only the u…
View article: Enabling Large-scale Heterogeneous Collaboration with Opportunistic Communications
Enabling Large-scale Heterogeneous Collaboration with Opportunistic Communications Open
Multi-robot collaboration in large-scale environments with limited-sized teams and without external infrastructure is challenging, since the software framework required to support complex tasks must be robust to unreliable and intermittent…
View article: TOPPQuad: Dynamically-Feasible Time Optimal Path Parametrization for Quadrotors
TOPPQuad: Dynamically-Feasible Time Optimal Path Parametrization for Quadrotors Open
Planning time-optimal trajectories for quadrotors in cluttered environments is a challenging, non-convex problem. This paper addresses minimizing the traversal time of a given collision-free geometric path without violating bounds on indiv…
View article: Selected papers from RSS2021
Selected papers from RSS2021 Open
View article: Safety Filter Design for Neural Network Systems via Convex Optimization
Safety Filter Design for Neural Network Systems via Convex Optimization Open
With the increase in data availability, it has been widely demonstrated that neural networks (NN) can capture complex system dynamics precisely in a data-driven manner. However, the architectural complexity and nonlinearity of the NNs make…
View article: Enhancing Sample Efficiency and Uncertainty Compensation in Learning-based Model Predictive Control for Aerial Robots
Enhancing Sample Efficiency and Uncertainty Compensation in Learning-based Model Predictive Control for Aerial Robots Open
The recent increase in data availability and reliability has led to a surge in the development of learning-based model predictive control (MPC) frameworks for robot systems. Despite attaining substantial performance improvements over their…
View article: Editorial
Editorial Open
View article: Stochastic Nonlinear Ensemble Modeling and Control for Robot Team Environmental Monitoring
Stochastic Nonlinear Ensemble Modeling and Control for Robot Team Environmental Monitoring Open
We seek methods to model, control, and analyze robot teams performing environmental monitoring tasks. During environmental monitoring, the goal is to have teams of robots collect various data throughout a fixed region for extended periods …
View article: Receding Horizon Control on the Broadcast of Information in Stochastic Networks
Receding Horizon Control on the Broadcast of Information in Stochastic Networks Open
This paper focuses on the broadcast of information on robot networks with stochastic network interconnection topologies. Problematic communication networks are almost unavoidable in areas where we wish to deploy multi-robotic systems, usua…
View article: Proportional Control for Stochastic Regulation on Allocation of Multi-Robots
Proportional Control for Stochastic Regulation on Allocation of Multi-Robots Open
Any strategy used to distribute a robot ensemble over a set of sequential tasks is subject to inaccuracy due to robot-level uncertainties and environmental influences on the robots' behavior. We approach the problem of inaccuracy during ta…
View article: Online Estimation of the Koopman Operator Using Fourier Features
Online Estimation of the Koopman Operator Using Fourier Features Open
Transfer operators offer linear representations and global, physically meaningful features of nonlinear dynamical systems. Discovering transfer operators, such as the Koopman operator, require careful crafted dictionaries of observables, a…
View article: Learning-enhanced Nonlinear Model Predictive Control using Knowledge-based Neural Ordinary Differential Equations and Deep Ensembles
Learning-enhanced Nonlinear Model Predictive Control using Knowledge-based Neural Ordinary Differential Equations and Deep Ensembles Open
Nonlinear model predictive control (MPC) is a flexible and increasingly popular framework used to synthesize feedback control strategies that can satisfy both state and control input constraints. In this framework, an optimization problem,…
View article: Towards Understanding Underwater Weather Events in Rivers Using Autonomous Surface Vehicles
Towards Understanding Underwater Weather Events in Rivers Using Autonomous Surface Vehicles Open
Climate change has increased the frequency and severity of extreme weather events such as hurricanes and winter storms. The complex interplay of floods with tides, runoff, and sediment creates additional hazards -- including erosion and th…
View article: LEARNEST: LEARNing Enhanced Model-based State ESTimation for Robots using Knowledge-based Neural Ordinary Differential Equations
LEARNEST: LEARNing Enhanced Model-based State ESTimation for Robots using Knowledge-based Neural Ordinary Differential Equations Open
State estimation is an important aspect in many robotics applications. In this work, we consider the task of obtaining accurate state estimates for robotic systems by enhancing the dynamics model used in state estimation algorithms. Existi…