2 citations · 3 across the 14 of their papers we have counts for
19 papers
Mobility-Budget-Constrained Submodular Maximization for Distributed Semantic Multi-Robot Exploration
Changxuan Yao, Sandilya Sai Garimella, Lu Gan +1
Multi-robot exploration under communication and mobility constraints requires balancing information gain with reachability. We present a distributed semantic exploration framework…
ATOM: Abstract Transition and Option Modeling - Experience-Informed Hierarchical Navigation
Changxuan Yao, Panagiotis Tsiotras
We propose ATOM (Abstract Transition and Option Modeling), a hierarchical navigation framework that combines higher-level graph planning with reusable lower-level option policies f…
Beyond Nominal Equilibria: Risk-Averse Multi-Population Mean-Field Games
Bhavini Jeloka, Siddhartha Ganguly, Panagiotis Tsiotras
Recent advances in mean-field games and its multi-population variants enable large-scale heterogeneous multi-agent systems to be modeled through representative agents and their ass…
Feedback Dominance Analysis for Pursuit-Evasion Games on Graphs
Yue Guan, Daigo Shishika, Dipankar Maity +2
This work identifies the dominance regions for discrete, simultaneous-move pursuit-evasion games on graphs. Existing geometric approaches provide efficient characterizations of win…
PDO-Split: A Real-Time Solver for Constrained Potential-Dominant Games
Zhiyuan Zhang, Yue Guan, Panagiotis Tsiotras
We present Potential-Dominant Operator Splitting (PDO-Split), a real-time generalized Nash equilibrium solver for constrained dynamic multi-agent problems with potential-dominant s…
Offline Nash Solvers Meet Online Tree Search in Multi-Agent Games on Graphs
Mukesh Kumar, Yue Guan, Panagiotis Tsiotras
Computing Nash equilibrium policies in multi-agent Pursuit-Evasion games (PEG) is challenging due to the exponential growth of the joint state and action spaces with the number of…
Performance-Driven Environment Abstraction with Multi-Timescale Learning
Yue Guan, Dipankar Maity, Panagiotis Tsiotras
We study performance-driven environment abstraction for decision-making in large Markov decision processes. Rather than preserving geometric or topological structure, we seek abstr…
Multi-Contact Force Estimation for Continuum Robots via Gaussian-Parameterized Factor Graphs
Aditya Prakash, Patricio A. Vela, Panagiotis Tsiotras
Continuum robots offer key advantages in navigating unstructured environments, but their safe operation requires accurate estimation of the external contact forces acting anywhere…
Collaborative Navigation and Exploration with -Sparse Gaussian Processes
Evangelos Psomiadis, Dipankar Maity, Panagiotis Tsiotras
Collaborative navigation of heterogeneous robots in unknown environments poses significant challenges due to sensing, communication, and computational limitations. In this work, a…
Robust Mean-Field Games with Risk Aversion and Bounded Rationality
Bhavini Jeloka, Yue Guan, Panagiotis Tsiotras
Recent advances in mean-field game literature enable the reduction of large-scale multi-agent problems to tractable interactions between a representative agent and a population dis…
A Dual Approach for Hierarchical Information-Theoretic Tree Abstractions
Daniel T. Larsson, Dipankar Maity, Panagiotis Tsiotras
In this paper, we consider establishing a formal connection between two distinct tree-abstraction problems inspired by the information-bottleneck (IB) method. Specifically, we cons…
Distributed Event-Triggered Distance-Based Formation Control for Multi-Agent Systems
Evangelos Psomiadis, Panagiotis Tsiotras
This paper addresses collaborative formation control for multi-agent systems with limited resources. We consider a team of robots tasked with achieving a desired formation from an…
Strategic Concealment of Environment Representations in Competitive Games
Yue Guan, Dipankar Maity, Panagiotis Tsiotras
This paper investigates the strategic concealment of environment representations used by players in competitive games. We consider a defense scenario in which one player (the Defen…
Communication-Aware Map Compression for Online Path-Planning: A Rate-Distortion Approach
Ali Reza Pedram, Evangelos Psomiadis, Dipankar Maity +1
This paper addresses the problem of collaborative navigation in an unknown environment, where two robots, referred to in the sequel as the Seeker and the Supporter, traverse the sp…
HCOA*: Hierarchical Class-ordered A* for Navigation in Semantic Environments
Evangelos Psomiadis, Panagiotis Tsiotras
This paper addresses the problem of robot navigation in mixed geometric/semantic 3D environments. Given a hierarchical representation of the environment, the objective is to naviga…
Learning Large-Scale Competitive Team Behaviors with Mean-Field Interactions
Bhavini Jeloka, Yue Guan, Panagiotis Tsiotras
While multi-agent reinforcement learning (MARL) has been proven effective across both collaborative and competitive tasks, existing algorithms often struggle to scale to large popu…
Communication-Aware Iterative Map Compression for Online Path-Planning
Evangelos Psomiadis, Ali Reza Pedram, Dipankar Maity +1
This paper addresses the problem of optimizing communicated information among heterogeneous, resource-aware robot teams to facilitate their navigation. In such operations, a mobile…
Factor Graph-Based Active SLAM for Spacecraft Proximity Operations
Lorenzo Ticozzi, Panagiotis Tsiotras
We investigate a scenario where a chaser spacecraft or satellite equipped with a monocular camera navigates in close proximity to a target spacecraft. The satellite's primary objec…
Neural Visibility Field for Uncertainty-Driven Active Mapping
Shangjie Xue, Jesse Dill, Pranay Mathur +3
This paper presents Neural Visibility Field (NVF), a novel uncertainty quantification method for Neural Radiance Fields (NeRF) applied to active mapping. Our key insight is that re…