7 papers · 1 filter
To Select or not to Select, that is the Question: Distilling Robot Skill Prediction into a Small Ensemble
Haechan Mark Bong, Simon Roy, Euhid Aman +1
As robot fleets become more heterogeneous, including humanoids, rovers, quadrupeds, and drones, selecting the right robot for a task becomes a core systems problem. We study robot…
Safe Aerial 3D Path Planning for Autonomous UAVs using Magnetic Potential Fields
Haechan Mark Bong, Giovanni Beltrame
Safe autonomous Uncrewed Aerial Vehicle (UAV) navigation in urban environments requires real-time path planning that avoids obstacles. MaxConvNet is a potential-field planner that…
Multi-Robot Decentralized Collaborative SLAM in Planetary Analogue Environments: Dataset, Challenges, and Lessons Learned
Pierre-Yves Lajoie, Karthik Soma, Haechan Mark Bong +4
Decentralized collaborative simultaneous localization and mapping (C-SLAM) is essential to enable multirobot missions in unknown environments without relying on preexisting localiz…
PEACE: Prompt Engineering Automation for CLIPSeg Enhancement for Safe-Landing Zone Segmentation
Haechan Mark Bong, Rongge Zhang, Antoine Robillard +1
Safe landing is essential in robotics applications, from industrial settings to space exploration. As artificial intelligence advances, we have developed PEACE (Prompt Engineering…
BlabberSeg: Real-Time Embedded Open-Vocabulary Aerial Segmentation
Haechan Mark Bong, Ricardo de Azambuja, Giovanni Beltrame
Real-time aerial image segmentation plays an important role in the environmental perception of Uncrewed Aerial Vehicles (UAVs). We introduce BlabberSeg, an optimized Vision-Languag…
Dynamic Open Vocabulary Enhanced Safe-landing with Intelligence (DOVESEI)
Haechan Mark Bong, Rongge Zhang, Ricardo de Azambuja +1
This work targets what we consider to be the foundational step for urban airborne robots, a safe landing. Our attention is directed toward what we deem the most crucial aspect of t…