5 papers
TRACE: Privacy-Preserving Next-Best-View Selection over Distributed 3D Gaussian-Splat Maps
Amirhossein Mollaei Khass, Athanasios Cosse, Qiyu Sun +1
Share the light, not the map. We study next-best-view selection for a team of robots, each of which builds its own 3D Gaussian Splatting map and keeps it private. A robot picks the…
Splat-CBF: Safe Next-Best-View Control in 3D Gaussian-Splat Maps
Amirhossein Mollaei Khass, Athanasios Cosse, Nader Motee
Where to look and how to move? A robot navigating an unmapped environment must do both at once, and the two goals pull against each other. The regions most worth observing are the…
SemSafe-3DGS: Semantic Risk-Aware Active Navigation in Uncertain 3D Gaussian Splatting Maps
Amirhossein Mollaei Khass, Athanasios Cosse, Nader Motee
Autonomous robots operating in partially observed environments must navigate safely while acquiring observations that improve future planning. Existing safety formulations generall…
Multi-Agent Next-Best-View Optimization for Risk-Averse Planning
Amirhossein Mollaei Khass, Vivek Pandey, Guangyi Liu +3
Multi-agent Next-Best-View (NBV) selection for safe path planning in uncertain and unknown environments requires informative, safety-aware, and efficient coordination. Centralized…
Conflict-Aware Active Perception and Control in 3D Gaussian Splatting Fields via Control Barrier Functions
Amirhossein Mollaei Khass, Athanasios Cosse, Vivek Pandey +1
Active perception in uncertain environments requires robots to navigate safely while acquiring informative observations to reduce map uncertainty. These objectives inherently confl…