Researchers have developed a new decentralized algorithm for coverage control in unknown spatial environments, utilizing Gaussian Processes (GPs). This method allows agents to autonomously determine their trajectories by minimizing a local cost function that balances predicted density and model uncertainty, inspired by the GP-UCB acquisition function. The algorithm operates in a fully decentralized manner, relying on local observations and neighbor communication, with agents updating their inducing points via a greedy selection strategy for scalable online GP updates. Its effectiveness has been demonstrated through simulations. AI
RANK_REASON This is a research paper detailing a novel algorithm for spatial coverage control using Gaussian Processes. [lever_c_demoted from research: ic=1 ai=0.7]
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →
