17 papers
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…
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…
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…
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…
Have We Scene It All? Scene Graph-Aware Deep Point Cloud Compression
Nikolaos Stathoulopoulos, Christoforos Kanellakis, George Nikolakopoulos
Efficient transmission of 3D point cloud data is critical for advanced perception in centralized and decentralized multi-agent robotic systems, especially nowadays with the growing…
A Minimal Subset Approach for Informed Keyframe Sampling in Large-Scale SLAM
Nikolaos Stathoulopoulos, Christoforos Kanellakis, George Nikolakopoulos
Typical LiDAR SLAM architectures feature a front-end for odometry estimation and a back-end for refining and optimizing the trajectory and map, commonly through loop closures. Howe…