most citedSafe Hierarchical Reinforcement Learning for CubeSat Task Scheduling Based on Energy Consumption

2 citations · 2 across the 9 of their papers we have counts for

collaborators

9 papers

cs.RO2024

Human-Centric Aware UAV Trajectory Planning in Search and Rescue Missions Employing Multi-Objective Reinforcement Learning with AHP and Similarity-Based Experience Replay

Mahya Ramezani, Jose Luis Sanchez-Lopez

The integration of Unmanned Aerial Vehicles (UAVs) into Search and Rescue (SAR) missions presents a promising avenue for enhancing operational efficiency and effectiveness. However…

cs.LG20232 cited

Safe Hierarchical Reinforcement Learning for CubeSat Task Scheduling Based on Energy Consumption

Mahya Ramezani, M. Amin Alandihallaj, Jose Luis Sanchez-Lopez +1

This paper presents a Hierarchical Reinforcement Learning methodology tailored for optimizing CubeSat task scheduling in Low Earth Orbits (LEO). Incorporating a high-level policy f…

cs.RO2023

Faster Optimization in S-Graphs Exploiting Hierarchy

Hriday Bavle, Jose Luis Sanchez-Lopez, Javier Civera +1

3D scene graphs hierarchically represent the environment appropriately organizing different environmental entities in various layers. Our previous work on situational graphs extend…

cs.RO2023

Graph-based Global Robot Simultaneous Localization and Mapping using Architectural Plans

Muhammad Shaheer, Jose Andres Millan-Romera, Hriday Bavle +3

In this paper, we propose a solution for graph-based global robot simultaneous localization and mapping (SLAM) using architectural plans. Before the start of the robot operation, t…

cs.RO2023

Multi S-graphs: A Collaborative Semantic SLAM architecture

Miguel Fernandez-Cortizas, Hriday Bavle, Jose Luis Sanchez-Lopez +2

Collaborative Simultaneous Localization and Mapping (CSLAM) is a critical capability for enabling multiple robots to operate in complex environments. Most CSLAM techniques rely on…

cs.LG2023

UAV Path Planning Employing MPC- Reinforcement Learning Method Considering Collision Avoidance

Mahya Ramezani, Hamed Habibi, Jose luis Sanchez Lopez +1

In this paper, we tackle the problem of Unmanned Aerial (UA V) path planning in complex and uncertain environments by designing a Model Predictive Control (MPC), based on a Long-Sh…