Matthew Gombolay
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View article: The effects of robot learning on human teachers for learning from demonstration
The effects of robot learning on human teachers for learning from demonstration Open
Learning from Demonstration (LfD) algorithms seek to enable end-users to teach robots new skills through human demonstration of a task. Previous studies have analyzed how robot failure affects human trust, but not in the context of the hum…
View article: Learning Interpretable Features from Interventions
Learning Interpretable Features from Interventions Open
View article: Proceedings of 1st Workshop on Advancing Artificial Intelligence through Theory of Mind
Proceedings of 1st Workshop on Advancing Artificial Intelligence through Theory of Mind Open
This volume includes a selection of papers presented at the Workshop on Advancing Artificial Intelligence through Theory of Mind held at AAAI 2025 in Philadelphia US on 3rd March 2025. The purpose of this volume is to provide an open acces…
View article: Towards Learning Scalable Agile Dynamic Motion Planning for Robosoccer Teams with Policy Optimization
Towards Learning Scalable Agile Dynamic Motion Planning for Robosoccer Teams with Policy Optimization Open
In fast-paced, ever-changing environments, dynamic Motion Planning for Multi-Agent Systems in the presence of obstacles is a universal and unsolved problem. Be it from path planning around obstacles to the movement of robotic arms, or in p…
View article: Use of Winsome Robots for Understanding Human Feedback (UWU)
Use of Winsome Robots for Understanding Human Feedback (UWU) Open
As social robots become more common, many have adopted cute aesthetics aiming to enhance user comfort and acceptance. However, the effect of this aesthetic choice on human feedback in reinforcement learning scenarios remains unclear. Previ…
View article: Compositional Instruction Following with Language Models and Reinforcement Learning
Compositional Instruction Following with Language Models and Reinforcement Learning Open
Combining reinforcement learning with language grounding is challenging as the agent needs to explore the environment while simultaneously learning multiple language-conditioned tasks. To address this, we introduce a novel method: the comp…
View article: AI-Based Decision Support for Perfusionists during Cardiopulmonary Bypass
AI-Based Decision Support for Perfusionists during Cardiopulmonary Bypass Open
View article: Monitoring of Perfusionists’ Cognitive Load and Stress and Patients’ Oxygen Delivery during Cardiopulmonary Bypass in Cardiac Surgery
Monitoring of Perfusionists’ Cognitive Load and Stress and Patients’ Oxygen Delivery during Cardiopulmonary Bypass in Cardiac Surgery Open
View article: Asynchronous Training of Mixed-Role Human Actors in a Partially-Observable Environment
Asynchronous Training of Mixed-Role Human Actors in a Partially-Observable Environment Open
In cooperative training, humans within a team coordinate on complex tasks, building mental models of their teammates and learning to adapt to teammates' actions in real-time. To reduce the often prohibitive scheduling constraints associate…
View article: ELEMENTAL: Interactive Learning from Demonstrations and Vision-Language Models for Reward Design in Robotics
ELEMENTAL: Interactive Learning from Demonstrations and Vision-Language Models for Reward Design in Robotics Open
Reinforcement learning (RL) has demonstrated compelling performance in robotic tasks, but its success often hinges on the design of complex, ad hoc reward functions. Researchers have explored how Large Language Models (LLMs) could enable n…
View article: Better Apprenticeship Learning with LLM Explanations
Better Apprenticeship Learning with LLM Explanations Open
As the population ages, care robots will play an increasing role in assisting caregiving by taking on repetitive or physically cumbersome activities. To effectively provide care, robotic agents must be able to meet the needs and preference…
View article: Generating CAD Code with Vision-Language Models for 3D Designs
Generating CAD Code with Vision-Language Models for 3D Designs Open
Generative AI has transformed the fields of Design and Manufacturing by providing efficient and automated methods for generating and modifying 3D objects. One approach involves using Large Language Models (LLMs) to generate Computer- Aided…
View article: Learning Wheelchair Tennis Navigation from Broadcast Videos with Domain Knowledge Transfer and Diffusion Motion Planning
Learning Wheelchair Tennis Navigation from Broadcast Videos with Domain Knowledge Transfer and Diffusion Motion Planning Open
In this paper, we propose a novel and generalizable zero-shot knowledge transfer framework that distills expert sports navigation strategies from web videos into robotic systems with adversarial constraints and out-of-distribution image tr…
View article: Learning Dynamics of a Ball with Differentiable Factor Graph and Roto-Translational Invariant Representations
Learning Dynamics of a Ball with Differentiable Factor Graph and Roto-Translational Invariant Representations Open
Robots in dynamic environments need fast, accurate models of how objects move in their environments to support agile planning. In sports such as ping pong, analytical models often struggle to accurately predict ball trajectories with spins…
View article: Learning Diverse Robot Striking Motions with Diffusion Models and Kinematically Constrained Gradient Guidance
Learning Diverse Robot Striking Motions with Diffusion Models and Kinematically Constrained Gradient Guidance Open
Advances in robot learning have enabled robots to generate skills for a variety of tasks. Yet, robot learning is typically sample inefficient, struggles to learn from data sources exhibiting varied behaviors, and does not naturally incorpo…
View article: Faster Model Predictive Control via Self-Supervised Initialization Learning
Faster Model Predictive Control via Self-Supervised Initialization Learning Open
Model Predictive Control (MPC) is widely used in robot control by optimizing a sequence of control outputs over a finite-horizon. Computational approaches for MPC include deterministic methods (e.g., iLQR and COBYLA), as well as sampling-b…
View article: Deep Learning Analysis of Surgical Video Recordings to Assess Nontechnical Skills
Deep Learning Analysis of Surgical Video Recordings to Assess Nontechnical Skills Open
Importance Assessing nontechnical skills in operating rooms (ORs) is crucial for enhancing surgical performance and patient safety. However, automated and real-time evaluation of these skills remains challenging. Objective To explore the f…
View article: Towards reconciling usability and usefulness of policy explanations for sequential decision-making systems
Towards reconciling usability and usefulness of policy explanations for sequential decision-making systems Open
Safefy-critical domains often employ autonomous agents which follow a sequential decision-making setup, whereby the agent follows a policy to dictate the appropriate action at each step. AI-practitioners often employ reinforcement learning…
View article: A Clinician-Centered Explainable Artificial Intelligence Framework for Decision Support in the Operating Theatre
A Clinician-Centered Explainable Artificial Intelligence Framework for Decision Support in the Operating Theatre Open
The integration of Artificial Intelligence (AI) into clinical decision support systems (CDSS) marks a significant advancement in the pursuit of enhanced patient care and operational efficiency in high-stakes environments, such as the opera…
View article: Designs for Enabling Collaboration in Human-Machine Teaming via Interactive and Explainable Systems
Designs for Enabling Collaboration in Human-Machine Teaming via Interactive and Explainable Systems Open
Collaborative robots and machine learning-based virtual agents are increasingly entering the human workspace with the aim of increasing productivity and enhancing safety. Despite this, we show in a ubiquitous experimental domain, Overcooke…
View article: Irregular optogenetic stimulation waveforms can induce naturalistic patterns of hippocampal spectral activity
Irregular optogenetic stimulation waveforms can induce naturalistic patterns of hippocampal spectral activity Open
Objective . Therapeutic brain stimulation is conventionally delivered using constant-frequency stimulation pulses. Several recent clinical studies have explored how unconventional and irregular temporal stimulation patterns could enable be…
View article: Editorial: Decision-making and planning for multi-agent systems
Editorial: Decision-making and planning for multi-agent systems Open
EDITORIAL article Front. Robot. AI, 24 May 2024Sec. Multi-Robot Systems Volume 11 - 2024 | https://doi.org/10.3389/frobt.2024.1422344
View article: Multi-Camera Asynchronous Ball Localization and Trajectory Prediction with Factor Graphs and Human Poses
Multi-Camera Asynchronous Ball Localization and Trajectory Prediction with Factor Graphs and Human Poses Open
The rapid and precise localization and prediction of a ball are critical for developing agile robots in ball sports, particularly in sports like tennis characterized by high-speed ball movements and powerful spins. The Magnus effect induce…
View article: Mixed-Initiative Human-Robot Teaming under Suboptimality with Online Bayesian Adaptation
Mixed-Initiative Human-Robot Teaming under Suboptimality with Online Bayesian Adaptation Open
For effective human-agent teaming, robots and other artificial intelligence (AI) agents must infer their human partner's abilities and behavioral response patterns and adapt accordingly. Most prior works make the unrealistic assumption tha…
View article: Efficient Trajectory Forecasting and Generation with Conditional Flow Matching
Efficient Trajectory Forecasting and Generation with Conditional Flow Matching Open
Trajectory prediction and generation are crucial for autonomous robots in dynamic environments. While prior research has typically focused on either prediction or generation, our approach unifies these tasks to provide a versatile framewor…
View article: Diffusion-Reinforcement Learning Hierarchical Motion Planning in Multi-agent Adversarial Games
Diffusion-Reinforcement Learning Hierarchical Motion Planning in Multi-agent Adversarial Games Open
Reinforcement Learning (RL)-based motion planning has recently shown the potential to outperform traditional approaches from autonomous navigation to robot manipulation. In this work, we focus on a motion planning task for an evasive targe…
View article: Enhancing Safety in Learning from Demonstration Algorithms via Control Barrier Function Shielding
Enhancing Safety in Learning from Demonstration Algorithms via Control Barrier Function Shielding Open
Learning from Demonstration (LfD) is a powerful method for non-roboticists end-users to teach robots new tasks, enabling them to customize the robot behavior. However, modern LfD techniques do not explicitly synthesize safe robot behavior,…
View article: Towards Balancing Preference and Performance through Adaptive Personalized Explainability
Towards Balancing Preference and Performance through Adaptive Personalized Explainability Open
As robots and digital assistants are deployed in the real world, these agents must be able to communicate their decision-making criteria to build trust, improve human-robot teaming, and enable collaboration. While the field of explainable …
View article: Interpretable Reinforcement Learning for Robotics and Continuous Control
Interpretable Reinforcement Learning for Robotics and Continuous Control Open
Interpretability in machine learning is critical for the safe deployment of learned policies across legally-regulated and safety-critical domains. While gradient-based approaches in reinforcement learning have achieved tremendous success i…
View article: Learning Efficient Diverse Communication for Cooperative Heterogeneous Teaming.
Learning Efficient Diverse Communication for Cooperative Heterogeneous Teaming. Open