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20242026
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cs.RO2026

A Graph-Based Reinforcement Learning Approach with Frontier Potential Based Reward for Safe Cluttered Environment Exploration

Gabriele Calzolari, Vidya Sumathy, Christoforos Kanellakis +1

Autonomous exploration of cluttered environments requires efficient exploration strategies that guarantee safety against potential collisions with unknown random obstacles. This pa…

cs.RO2026

xFLIE: Leveraging Actionable Hierarchical Scene Representations for Autonomous Semantic-Aware Inspection Missions

Vignesh Kottayam Viswanathan, Mario A. V. Saucedo, Sumeet Gajanan Satpute +2

We present a novel architecture aimed towards incremental construction and exploitation of a hierarchical 3D scene graph representation during semantic-aware inspection missions. I…

cs.RO2026

An Adaptive Inspection Planning Approach Towards Routine Monitoring in Uncertain Environments

Vignesh Kottayam Viswanathan, Yifan Bai, Scott Fredriksson +3

In this work, we present a hierarchical framework designed to support robotic inspection under environment uncertainty. By leveraging a known environment model, existing methods pl…

cs.RO2026

Safe Heterogeneous Multi-Agent RL with Communication Regularization for Coordinated Target Acquisition

Gabriele Calzolari, Vidya Sumathy, Christoforos Kanellakis +1

This paper introduces a decentralized multi-agent reinforcement learning framework enabling structurally heterogeneous teams of agents to jointly discover and acquire randomly loca…

cs.RO2025

Platform-Agnostic Reinforcement Learning Framework for Safe Exploration of Cluttered Environments with Graph Attention

Gabriele Calzolari, Vidya Sumathy, Christoforos Kanellakis +1

Autonomous exploration of obstacle-rich spaces requires strategies that ensure efficiency while guaranteeing safety against collisions with obstacles. This paper investigates a nov…

cs.RO2025

SPADE: Towards Scalable Path Planning Architecture on Actionable Multi-Domain 3D Scene Graphs

Vignesh Kottayam Viswanathan, Akash Patel, Mario Alberto Valdes Saucedo +3

In this work, we introduce SPADE, a path planning framework designed for autonomous navigation in dynamic environments using 3D scene graphs. SPADE combines hierarchical path plann…