Fast, Smooth, and Safe: Implicit Control Barrier Functions Through Reach-Avoid Differential Dynamic Programming

Athindran Ramesh Kumar; Kai Chieh Hsu; Peter J. Ramadge; Jaime F. Fisac

doi:10.1109/LCSYS.2023.3292132

Fast, Smooth, and Safe: Implicit Control Barrier Functions Through Reach-Avoid Differential Dynamic Programming

Athindran Ramesh Kumar, Kai Chieh Hsu, Peter J. Ramadge, Jaime F. Fisac

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Safety is a central requirement for autonomous system operation across domains. Hamilton-Jacobi (HJ) reachability analysis can be used to construct 'least-restrictive' safety filters that result in infrequent, but often extreme, control overrides. In contrast, control barrier function (CBF) methods apply smooth control corrections to guard the system against an often conservative safety boundary. This letter provides an online scheme to construct an implicit CBF through HJ reach-avoid differential dynamic programming in a receding-horizon framework, enabling smooth safety filtering with infinite-time safety guarantees. Simulations with the Dubins car and 5D bicycle dynamics demonstrate the scheme's ability to preserve safety smoothly without the conservativeness of handcrafted CBFs.

Original language	English (US)
Pages (from-to)	2994-2999
Number of pages	6
Journal	IEEE Control Systems Letters
Volume	7
DOIs	https://doi.org/10.1109/LCSYS.2023.3292132
State	Published - 2023
Externally published	Yes

All Science Journal Classification (ASJC) codes

Control and Optimization
Control and Systems Engineering

Keywords

Autonomous systems
control barrier functions
reach-avoid analysis

Access to Document

10.1109/LCSYS.2023.3292132

Cite this

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title = "Fast, Smooth, and Safe: Implicit Control Barrier Functions Through Reach-Avoid Differential Dynamic Programming",

abstract = "Safety is a central requirement for autonomous system operation across domains. Hamilton-Jacobi (HJ) reachability analysis can be used to construct 'least-restrictive' safety filters that result in infrequent, but often extreme, control overrides. In contrast, control barrier function (CBF) methods apply smooth control corrections to guard the system against an often conservative safety boundary. This letter provides an online scheme to construct an implicit CBF through HJ reach-avoid differential dynamic programming in a receding-horizon framework, enabling smooth safety filtering with infinite-time safety guarantees. Simulations with the Dubins car and 5D bicycle dynamics demonstrate the scheme's ability to preserve safety smoothly without the conservativeness of handcrafted CBFs.",

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AU - Hsu, Kai Chieh

AU - Ramadge, Peter J.

AU - Fisac, Jaime F.

PY - 2023

Y1 - 2023

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AB - Safety is a central requirement for autonomous system operation across domains. Hamilton-Jacobi (HJ) reachability analysis can be used to construct 'least-restrictive' safety filters that result in infrequent, but often extreme, control overrides. In contrast, control barrier function (CBF) methods apply smooth control corrections to guard the system against an often conservative safety boundary. This letter provides an online scheme to construct an implicit CBF through HJ reach-avoid differential dynamic programming in a receding-horizon framework, enabling smooth safety filtering with infinite-time safety guarantees. Simulations with the Dubins car and 5D bicycle dynamics demonstrate the scheme's ability to preserve safety smoothly without the conservativeness of handcrafted CBFs.

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Fast, Smooth, and Safe: Implicit Control Barrier Functions Through Reach-Avoid Differential Dynamic Programming

Abstract

All Science Journal Classification (ASJC) codes

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