Leading the AI Revolution: 2026 Trends and Insights from Saudi Arabia & UAE - Deloitte
Leading the AI Revolution: 2026 Trends and Insights from Saudi Arabia & UAE Deloitte
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IA-TIGRIS: An Incremental and Adaptive Sampling-Based Planner for Online Informative Path Planning
arXiv:2502.15961v3 Announce Type: replace Abstract: Planning paths that maximize information gain for robotic platforms has wide-ranging applications and significant potential impact. To effectively adapt to real-time data collection, informative path planning must be computed online and be responsive to new observations. In this work, we present IA-TIGRIS (Incremental and Adaptive Tree-based Information Gathering Using Informed Sampling), which is an incremental and adaptive sampling-based informative path planner designed for real-time onboard execution. Our approach leverages past planning efforts through incremental refinement while continuously adapting to updated belief maps. We additionally present detailed implementation and optimization insights to facilitate real-world deployment
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