activity
20242026
collaborators

8 papers

cs.RO2026

Communication-Free Collective Navigation for a Swarm of UAVs via LiDAR-Based Deep Reinforcement Learning

Myong-Yol Choi, Hankyoul Ko, Hanse Cho +4

This paper presents a deep reinforcement learning (DRL) based controller for collective navigation of unmanned aerial vehicle (UAV) swarms in communication-denied environments, ena…

cs.RO2025

Optimizing Indoor Farm Monitoring Efficiency Using UAV: Yield Estimation in a GNSS-Denied Cherry Tomato Greenhouse

Taewook Park, Jinwoo Lee, Hyondong Oh +2

As the agricultural workforce declines and labor costs rise, robotic yield estimation has become increasingly important. While unmanned ground vehicles (UGVs) are commonly used for…

cs.MA2025

Kalman Filter-Based Distributed Gaussian Process for Unknown Scalar Field Estimation in Wireless Sensor Networks

Jaemin Seo, Geunsik Bae, Hyondong Oh

In this letter, we propose an online scalar field estimation algorithm of unknown environments using a distributed Gaussian process (DGP) framework in wireless sensor networks (WSN…

cs.RO2025

Doppler Correspondence: Non-Iterative Scan Matching With Doppler Velocity-Based Correspondence

Jiwoo Kim, Geunsik Bae, Changseung Kim +3

Achieving successful scan matching is essential for LiDAR odometry. However, in challenging environments with adverse weather conditions or repetitive geometric patterns, LiDAR odo…

cs.RO2025

RAPID: Robust and Agile Planner Using Inverse Reinforcement Learning for Vision-Based Drone Navigation

Minwoo Kim, Geunsik Bae, Jinwoo Lee +5

This paper introduces a learning-based visual planner for agile drone flight in cluttered environments. The proposed planner generates collision-free waypoints in milliseconds, ena…

cs.RO2025

EKF-Based Radar-Inertial Odometry with Online Temporal Calibration

Changseung Kim, Geunsik Bae, Woojae Shin +2

Accurate time synchronization between heterogeneous sensors is crucial for ensuring robust state estimation in multi-sensor fusion systems. Sensor delays often cause discrepancies…