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SenseSwarm: Swarm Exploration via Neural Structure Estimation with Shared World-Anticipation for Rapid Mapping
Haohua Que, Haojia Gao, Mingkai Liu +7
A robot swarm covers a building faster with more robots, but the map is only as complete as the space the robots have physically visited. We target the amount of an unknown buildin…
Retrieve in Time, Correct in Frequency
Yuze Fan, Yue Cao, Pengjie Gao +7
Frozen vision-language-action (VLA) policies generate temporally extended action chunks, but long-horizon manipulation remains vulnerable to accumulated execution error and visual…
SPACE: Swarm Pheromone Fields for Adaptive Collision-Aware Exploration
Haohua Que, Haojia Gao, Mingkai Liu +3
Massive robot swarms can explore unknown environments quickly, but adding robots eventually stops helping. Doorways and dense traffic create congestion, increasing inter-robot cont…
ACEsplat: Accelerated 3D Gaussian Scene Regression via RGB and Poses Only
Mingkai Liu, Haohua Que, Dikai Fan +7
Per-scene 3D Gaussian Splatting (3DGS) enables high-fidelity rendering, but practical robotic and AR scene capture pipelines often depend on external geometric initialization (e.g.…
Mapping at First Sense: A Lightweight Neural Network-Based Indoor Structures Prediction Method for Robot Autonomous Exploration
Haojia Gao, Haohua Que, Kunrong Li +7
Autonomous exploration in unknown environments is a critical challenge in robotics, particularly for applications such as indoor navigation, search and rescue, and service robotics…