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Decentralized Safety for Aggressively Maneuvering Multi-Robot Interactions

Phillip Rivera-Ortiz, Marin Kobilarov

发表年份
2022
引用次数
2

摘要

This work provides a decentralized approach to safety by combining tools from control barrier functions (CBF) and nonlinear model predictive control (NMPC). It is shown how leveraging backup safety controllers allows for the robust implementation of CBF over the NMPC computation horizon, ensuring safety in nonlinear systems with actuation constraints. A leader-follower approach to control barrier functions (LF- CBF) enforcement will be introduced as a strategy to enable a robot leader, in a multi-robot interactions, to complete its task in minimum time, hence aggressively maneuvering. An algorithmic implementation of the proposed solution is provided and safety is verified via simulation.

关键词

Model predictive controlBackupComputer scienceRobotTask (project management)Control engineeringComputationControl theory (sociology)Nonlinear systemNonlinear model

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