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M. Ani Hsieh

43 accepted papers

2026

Air-Ground Collaboration for Language-Specified Missions in Unknown Environments (I)

Fernando Cladera, Zachary Ravichandran, Jason Hughes, Varun Murali, Carlos Nieto-Granda, M. Ani Hsieh +3
ICRA 2026poster

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, realizing language-guided robotic teams requires overcoming si…

Cited by 0Scholar ↗
2026

Multi-Robot Multi-Source Localization in Complex Flows with Physics-Preserving Environment Models

Benjamin Shaffer, Victoria Edwards, Brooks Kinch, Nathaniel Trask, M. Ani Hsieh
ICRA 2026poster

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, resulting in sporadic and intermittent sensor readings, and com…

Cited by 0Source ↗PDF ↗Scholar ↗
2026

Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs

Benjamin Shaffer, Shawn Koohy, Brooks Kinch, M. Ani Hsieh, Nathaniel Trask
ICML 2026poster

We aim to develop physics foundation models for science and engineering that provide real-time solutions to Partial Differential Equations (PDEs) which preserve structure and accuracy under adaptation to unseen geometries. To this end, we introduce General-Geometry Neural Whitney Forms (Geo-NeWF): a…

Cited by 0Source ↗Scholar ↗
2025

EvMAPPER: High-Altitude Orthomapping with Event Cameras

Fernando Cladera, Kenneth Chaney, M. Ani Hsieh, Camillo J. Taylor, Vijay Kumar
ICRA 2025

Traditionally, unmanned aerial vehicles (UAVs) rely on CMOS-based cameras to collect images about the world below. One of the most successful applications of UAVs is to generate orthomosaics or orthomaps, in which a series of images are integrated to develop a larger map. However, using CMOS-based c

Cited by 3Source ↗Scholar ↗
2025

Flying Quadrotors in Tight Formations Using Learning-Based Model Predictive Control

Kong Yao Chee, Pei-An Hsieh, George J. Pappas, M. Ani Hsieh
ICRA 2025

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 learning tools can potentially be used to derive models that captur

Cited by 6Source ↗Scholar ↗
2025

KoopMotion: Learning Almost Divergence Free Koopman Flow Fields for Motion Planning

Alice Kate Li, Thales C. Silva, Victoria Edwards, Vijay Kumar, M. Ani Hsieh
CoRL 2025poster

In this work, we propose a novel flow field-based motion planning method that drives a robot from any initial state to a desired reference trajectory such that it converges to the trajectory's end point. Despite demonstrated efficacy in using Koopman operator theory for modeling dynamical systems,…

Cited by 0Source ↗Scholar ↗
2024

Communication-Constrained Multi-Robot Exploration with Intermittent Rendezvous

Alysson Ribeiro Da Silva, Luiz Chaimowicz, Thales C. Silva, M. Ani Hsieh
IROS 2024poster

Communication constraints can significantly impact robots’ ability to share information, coordinate their movements, and synchronize their actions, thus limiting coordination in Multi-Robot Exploration (MRE) applications. In this work, we address these challenges by modeling the MRE application as a…

Cited by 2Source ↗code ↗Scholar ↗
2024

Enabling Large-scale Heterogeneous Collaboration with Opportunistic Communications

Fernando Cladera, Zachary Ravichandran, Ian D. Miller, M. Ani Hsieh, C. J. Taylor, Vijay Kumar
ICRA 2024poster

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 communication links. In this work, we present MOCHA (Multi-r…

Cited by 7Source ↗Scholar ↗
2024

TOPPQuad: Dynamically-Feasible Time-Optimal Path Parametrization for Quadrotors

Katherine Mao, Igor Spasojevic, M. Ani Hsieh, Vijay Kumar
IROS 2024

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 actuation bounds of the vehicle. Previous approaches have either relied on c

Cited by 5Source ↗Scholar ↗
2023

Energy-Efficient Team Orienteering Problem in the Presence of Time-Varying Ocean Currents

Ariella Mansfield, Douglas G. Macharet, M. Ani Hsieh
IROS 2023poster

Autonomous Marine Vehicles (AMVs) have gained interest for scientific and commercial applications, including pipeline and algae bloom monitoring, contaminant tracking, and ocean debris removal. The Team Orienteering Problem (TOP) is relevant in this context as Multi-Robot Systems (MRSs) allow for be…

Cited by 2Source ↗Scholar ↗
2023

Enhancing Sample Efficiency and Uncertainty Compensation in Learning-Based Model Predictive Control for Aerial Robots

Kong Yao Chee, Thales C. Silva, M. Ani Hsieh, George J. Pappas
IROS 2023poster

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 non-learning counterparts, many of these frameworks rely on…

Cited by 7Source ↗Scholar ↗
2023

Flow-Based Rendezvous and Docking for Marine Modular Robots in Gyre-Like Environments

Gedaliah Knizhnik, Peihan Li, Mark Yim, M. Ani Hsieh
ICRA 2023poster

Modular self-assembling systems typically assume that modules are present to assemble. But in sparsely observed ocean environments modules of an aquatic modular robotic system may be separated by distances they do not have the energy to cross, and the information needed for optimal path planning is…

Cited by 6Source ↗Scholar ↗
2023

LEARNEST: LEARNing Enhanced Model-based State ESTimation for Robots using Knowledge-based Neural Ordinary Differential Equations

Kong Yao Chee, M. Ani Hsieh
ICRA 2023poster

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. Existing frameworks such as moving horizon estimation (MHE) and the…

Cited by 4Source ↗Scholar ↗
2023

On Collaborative Robot Teams for Environmental Monitoring: A Macroscopic Ensemble Approach

Victoria Edwards, Thales C. Silva, Bharg Mehta, Jasleen Dhanoa, M. Ani Hsieh
IROS 2023poster

With the rapidly changing climate and an increase in extreme weather events, it is necessary to have better methods to monitor and study the impacts of these phenomena on urban river environments. Multi-robot environmental monitoring has long focused on strategies that assign individual robots to di…

Cited by 2Source ↗Scholar ↗
2023

Trajectory Planning for the Bidirectional Quadrotor as a Differentially Flat Hybrid System

Katherine Mao, Jake Welde, M. Ani Hsieh, Vijay Kumar
ICRA 2023poster

The use of bidirectional propellers provides quadrotors with greater maneuverability which is advantageous in constrained environments. This paper addresses the development of a trajectory planning algorithm for quadrotors with bidirectional motors. Previous work has shown that the property of diffe…

Cited by 4Source ↗Scholar ↗
2022

Adaptive Sampling of Latent Phenomena using Heterogeneous Robot Teams (ASLaP-HR)

Matthew Malencia, Sandeep Manjanna, M. Ani Hsieh, George Pappas, Vijay Kumar
IROS 2022poster

In this paper, we present an online adaptive planning strategy for a team of robots with heterogeneous sensors to sample from a latent spatial field using a learned model for decision making. Current robotic sampling methods seek to gather information about an observable spatial field. However, many…

Cited by 11Source ↗code ↗Scholar ↗
2022

EV-Catcher: High-Speed Object Catching Using Low-Latency Event-Based Neural Networks

Ziyun Wang, Fernando Cladera Ojeda, Anthony Bisulco, Daewon Lee, Camillo J. Taylor, Kostas Daniilidis +3
RA-L 2022

Event-based sensors have recently drawn increasing interest in robotic perception due to their lower latency, higher dynamic range, and lower bandwidth requirements compared to standard CMOS-based imagers. These properties make them ideal tools for real-time perception tasks in highly dynamic enviro

Cited by 26Source ↗Scholar ↗
2022

Energy-efficient Orienteering Problem in the Presence of Ocean Currents

Ariella Mansfield, Douglas G. Macharet, M. Ani Hsieh
IROS 2022poster

In many environmental monitoring applications robots are often tasked to visit various distinct locations to make observations and/or collect specific measurements. The problem of scheduling and assigning robots to the various tasks and planning feasible paths for the robots can be posed as an Orien…

Cited by 7Source ↗Scholar ↗
2022

KNODE-MPC: A Knowledge-Based Data-Driven Predictive Control Framework for Aerial Robots

Kong Yao Chee, Tom Z. Jiahao, M. Ani Hsieh
RA-L 2022

In this letter, we consider the problem of deriving and incorporating accurate dynamic models for model predictive control (MPC) with an application to quadrotor control. MPC relies on precise dynamic models to achieve the desired closed-loop performance. However, the presence of uncertainties in co

Cited by 95Source ↗Scholar ↗
2022

Learning and Leveraging Features in Flow-Like Environments to Improve Situational Awareness

Tahiya Salam, Victoria M. Edwards, M. Ani Hsieh
RA-L 2022

This letter studies how global dynamics and knowledge of high-level features can inform decision-making for robots in flow-like environments. Specifically, we investigate how coherent sets, an environmental feature found in these environments, inform robot awareness within these scenarios. The propo

Cited by 7Source ↗Scholar ↗
2022

NODEO: A Neural Ordinary Differential Equation Based Optimization Framework for Deformable Image Registration

Yifan Wu, Tom Z. Jiahao, Jiancong Wang, Paul A. Yushkevich, M. Ani Hsieh, James C. Gee
CVPR 2022poster

Deformable image registration (DIR), aiming to find spatial correspondence between images, is one of the most critical problems in the domain of medical image analysis. In this paper, we present a novel, generic, and accurate diffeomorphic image registration framework that utilizes neural ordinary d…

Cited by 43PDF ↗code ↗Scholar ↗
2022

Online Dynamics Learning for Predictive Control with an Application to Aerial Robots

Tom Z. Jiahao, Kong Yao Chee, M. Ani Hsieh
CoRL 2022poster

In this work, we consider the task of improving the accuracy of dynamic models for model predictive control (MPC) in an online setting. Although prediction models can be learned and applied to model-based controllers, these models are often learned offline. In this offline setting, training data is…

Cited by 21Source ↗code ↗Scholar ↗
2021

Multi-robot Scheduling for Environmental Monitoring as a Team Orienteering Problem

Ariella Mansfield, Sandeep Manjanna, Douglas G. Macharet, M. Ani Hsieh
IROS 2021poster

In this paper, we propose an evolutionary algorithm for solving the multi-robot orienteering problem where a team of cooperative robots aims to maximize the total information collected by visiting a subset of given nodes within a fixed budget on travel costs. Multi-robot orienteering problems are re…

Cited by 21Source ↗Scholar ↗
2020

A Topological Approach to Path Planning for a Magnetic Millirobot

Ariella Mansfield, Dhanushka Kularatne, Edward Steager, M. Ani Hsieh
IROS 2020poster

We present a path planning strategy for a magnetic millirobot where the nonlinearities in the external magnetic force field (MFF) are encoded in the graph used for planning. The strategy creates a library of candidate MFFs and characterizes their topologies by identifying the unstable manifolds in t…

Cited by 1Source ↗Scholar ↗
2020

Asynchronous Adaptive Sampling and Reduced-Order Modeling of Dynamic Processes by Robot Teams via Intermittently Connected Networks

Hannes Rovina, Tahiya Salam, Yiannis Kantaros, M. Ani Hsieh
IROS 2020poster

This work presents an asynchronous multi-robot adaptive sampling strategy through the synthesis of an intermittently connected mobile robot communication network. The objective is to enable a team of robots to adaptively sample and model a nonlinear dynamic spatiotemporal process. By employing an in…

Cited by 5Source ↗Scholar ↗
2020

Nonlinear Synchronization Control for Short-Range Mobile Sensors Drifting in Geophysical Flows

Cong Wei, Herbert G. Tanner, M. Ani Hsieh
ICRA 2020poster

This paper presents a synchronization controller for mobile sensors that are minimally actuated and can only communicate with each other over a very short range. This work is motivated by ocean monitoring applications where large-scale sensor networks consisting of drifters with minimal actuation ca…

Cited by 2Source ↗Scholar ↗
2019

Evaluating the Effectiveness of Perspective Aware Planning with Panoramas

Daniel Mox, Anthony Cowley, M. Ani Hsieh, C. J. Taylor
ICRA 2019poster

In this work, we present an information based exploration strategy tailored for the generation of high resolution 3D maps. We employ RGBD panoramas because they have been shown to provide memory efficient high quality representations of space. Robots explore the environment by selecting locations wi…

Cited by 1Source ↗Scholar ↗
2018

Exploiting Stochasticity for the Control of Transitions in Gyre Flows

Dhanushka Kularatne, Eric Forgoston, M. Ani Hsieh
RSS 2018poster

We present a control strategy to control the inter-gyre switching time of an agent operating in a gyre flow. The proposed control strategy exploits the stochasticity of the underlying environment to affect inter-gyre transitions. We show how control can be used to enhance or abate the mean escape ti…

Cited by 5Source ↗PDF ↗Scholar ↗
2018

Optimal Path Planning in Time-Varying Flows Using Adaptive Discretization

Dhanushka Kularatne, Subhrajit Bhattacharya, M. Ani Hsieh
RA-L 2018

Autonomous marine vehicles (AMVs) are typically deployed for long periods of time in the ocean to monitor different physical, chemical, and biological processes. Given their limited energy budgets, it makes sense to consider motion plans that leverage the dynamics of the surrounding flow field so as

Cited by 37Source ↗Scholar ↗
2018

Optimal Path Planning in Time-Varying Flows with Forecasting Uncertainties

Dhanushka Kularatne, Hadi Hajieghrary, M. Ani Hsieh
ICRA 2018poster

Uncertainties in flow models have to be explicitly considered for effective path planning in marine environments. In this paper, we present two methods to compute minimum expected cost policies and paths over an uncertain flow model. The first method based on a Markov Decision Process computes a min…

Cited by 36Source ↗Scholar ↗
2017

Cooperative transport of a buoyant load: A differential geometric approach

Hadi Hajieghrary, Dhanushka Kularatne, M. Ani Hsieh
IROS 2017poster

We present a differential geometric approach towards the synthesis of cooperative controllers for a team of autonomous surface vehicles transporting a buoyant load. We are interested in cooperative transport of large objects by teams of autonomous surface vehicles (ASVs) operating in marine and litt…

Cited by 13Source ↗Scholar ↗
2017

Intrusion detection for stochastic task allocation in robot swarms

Florian Maushart, Amanda Prorok, M. Ani Hsieh, Vijay Kumar
IROS 2017poster

We present a novel framework for integrity analysis of swarm robotic systems using the symmetric Kullback-Leibler Divergence. The objective is to understand a robot swarm's vulnerability to malicious intrusion and to develop the necessary computational tools that would detect the presence of malicio…

Cited by 6Source ↗Scholar ↗
2016

A triangle histogram for object classification by tactile sensing

Mabel M. Zhang, Monroe D. Kennedy, M. Ani Hsieh, Kostas Daniilidis
IROS 2016poster

We present a new descriptor for tactile 3D object classification. It is invariant to object movement and simple to construct, using only the relative geometry of points on the object surface. We demonstrate successful classification of 185 objects in 10 categories, at sparse to dense surface samplin…

Cited by 35Source ↗Scholar ↗
2015

Zig-zag wanderer: Towards adaptive tracking of time-varying coherent structures in the ocean

Dhanushka Kularatne, Ryan N. Smith, M. Ani Hsieh
ICRA 2015poster

Similar to the atmosphere, coherent structures, e.g., fronts, exist in the ocean. These frontal structures are known to be highly productive, supporting the whole spectrum of marine life. Ocean fronts are dynamic in time and space, and are a key component to a comprehensive knowledge of ocean dynami…

Cited by 12Source ↗Scholar ↗