Event
CA-BRF: Backup-Recoverability Filter for Heterogeneous Multi-Robot Navigation
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Joonkyung Kim and co-authors propose the Capability-Aware Backup-Recoverability Filter (CA-BRF) for heterogeneous multi-robot navigation: a backup-recoverable set is constructed in a shared Cartesian operating space, and candidate controls are screened against it so that each robot retains a certified recovery maneuver consistent with its own kinematic and actuation constraints. The authors state that the method selects feasible action interpolations between candidate actions and backup actions and coordinates simultaneous interactions, thereby guaranteeing recursive feasibility and safety of the discrete-time closed-loop system even when the nominal safety-constrained optimization is infeasible. The authors state that the method has been validated in simulation, covering up to 30 heterogeneous robots, with experiments involving five different kinematic classes.
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- CA-BRF: A Capability-Aware Backup-Recoverability Filter for Heterogeneous Multi-Robot Navigation
The authors propose a Capability-Aware Backup-Recoverability Filter (CA-BRF) that constructs a backup-recoverable set in a shared Cartesian operational space and uses it to screen candidate controls, so that each robot retains a certified recovery maneuver consistent with its own kinematic and actuation constraints. The method selects admissible interpolations between candidate and backup actions and coordinates simultaneous interactions, thereby guaranteeing recursive feasibility and safety of the discrete-time closed-loop system even when the nominal safety-constrained optimization is infeasible. Simulations cover up to 30 heterogeneous robots, and experiments involve five distinct kinematic classes.
arXiv cs.RO ·
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