首页|Research Data from Brigham Young University Update Understanding of Robotics and Automation (Multi-agent Path Planning for Level Set Estimation Using B-splines and Differential Flatness)
Research Data from Brigham Young University Update Understanding of Robotics and Automation (Multi-agent Path Planning for Level Set Estimation Using B-splines and Differential Flatness)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Robotics - Robotics an d Automation is the subject of a report. According to news reporting originating in Provo, Utah, by NewsRx journalists, research stated, “In this letter, we pre sent a decentralized multi-agent path planning algorithm for level set estimatio n (LSE) and environmental monitoring missions. The planned paths are parameteriz ed using B-splines and optimized using a novel objective function designed for L SE path planning that accounts for the exploration/exploitation trade-off while allowing the use of a gradient-based optimizer.” Financial support for this research came from Center for Autonomous Air Mobility and Sensing. The news reporters obtained a quote from the research from Brigham Young Univers ity, “We use the differential flatness property of the unicycle model to formula te constraints for our path optimization that ensure planned paths are kinematic ally feasible. We also employ a block coordinate ascent (BCA) algorithm that ena bles multi-agent coordination in exploring the environment.”
Provo, Utah, United States, North and Ce ntral America, Robotics and Automation, Robotics, Brigham Young University
NETL
NSTL
