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autonomous driving machine learning
[2025 – 2026] Building an open synthetic benchmark and reference baselines for V2X cooperative 3D semantic occupancy prediction, so that connected vehicles and roadside infrastructure can jointly reconstruct dense, semantically rich representations of the driving scene.
machine learning uav
[2024 – 2026] Unmanned Aerial Vehicles (UAVs) and Autonomous Mobile Robots (AMRs) are foundational platforms for 6G-era applications spanning aerial surveillance, disaster response, warehouse logistics, and precision agriculture. Autonomous trajectory planning under interference, partial observability, energy constraints, and multi-agent coordination remains a central bottleneck.
autonomous driving v2x
[2023 – 2026] Investigating the Smart Pole Interaction Unit (SPIU) as an infrastructure-side interface that complements vehicle eHMI to reduce pedestrian negotiation burden and support clearer, safer interaction with autonomous vehicles in shared spaces.
open source
v2x
[2023 – 2026] Developing a robust, channel-adaptive vehicular localization and tracking system utilizing mmWave MIMO, RIS, and OTFS technologies for environments where GPS is unavailable.
