5 papers
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…
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…
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…
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…
Enhancing Exploration Efficiency using Uncertainty-Aware Information Prediction
Seunghwan Kim, Heejung Shin, Gaeun Yim +2
Autonomous exploration is a crucial aspect of robotics, enabling robots to explore unknown environments and generate maps without prior knowledge. This paper proposes a method to e…