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Control Barrier Functions With Circulation Inequalities
Control barrier functions (CBFs) when paired with quadratic programming (QP) offer an increasingly popular framework for control considering critical safety constraints. However, being closely related to artificial potential fields, they suffer from the classical stable spurious equilibrium point pr...
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Published in: | IEEE transactions on control systems technology 2024-07, Vol.32 (4), p.1426-1441 |
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creator | Goncalves, Vinicius Mariano Krishnamurthy, Prashanth Tzes, Anthony Khorrami, Farshad |
description | Control barrier functions (CBFs) when paired with quadratic programming (QP) offer an increasingly popular framework for control considering critical safety constraints. However, being closely related to artificial potential fields, they suffer from the classical stable spurious equilibrium point problem, in which the controller can fail to drive the system to the goal. The main contribution of this article is showing that this problem can be mitigated by introducing a circulation inequality as a constraint, which forces the system to explicitly circulate obstacles under some conditions. This circulation is introduced in the configuration space and is simple to implement once we have the CBF-constraint, adding a negligible complexity to the resulting optimization problem. Theoretical guarantees are provided for this framework, indicating, under appropriate conditions, the feasibility of the resulting optimization problem, continuity of the control input, characterization of the equilibrium points, a weak form of Lyapunov stability, and uniqueness of the equilibrium points. The provided experimental studies showcase the overall properties and applicability in different scenarios. |
doi_str_mv | 10.1109/TCST.2024.3372802 |
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The provided experimental studies showcase the overall properties and applicability in different scenarios.</description><subject>Circulation</subject><subject>Collision avoidance</subject><subject>Equilibrium</subject><subject>Lyapunov methods</subject><subject>Motion control</subject><subject>Navigation</subject><subject>Optimization</subject><subject>Potential fields</subject><subject>Quadratic programming</subject><subject>quadratic programming (QP)</subject><subject>Robot control</subject><subject>Safety</subject><issn>1063-6536</issn><issn>1558-0865</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNpNkE1LxDAQhoMouH78AMFDwXPXZKb5OmpxdWHBgyseQ5qmmKW2u0l78N_bsnvwNC_D887AQ8gdo0vGqH7clh_bJVAologSFIUzsmCcq5wqwc-nTAXmgqO4JFcp7ShlBQe5ILLsuyH2bfZsYww-Zquxc0Pou5R9heE7K0N0Y2vnTbbu_GG0bRiCTzfkorFt8reneU0-Vy_b8i3fvL-uy6dN7qAQQy4r4FRoK6SuLQcBHJuC2hqFtVozZFgBq5myEp3WyhbONSBRVd5XtpYar8nD8e4-9ofRp8Hs-jF200uDVAKCFJxNFDtSLvYpRd-YfQw_Nv4aRs3sx8x-zOzHnPxMnftjJ3jv__GFBMkU_gHip2CN</recordid><startdate>20240701</startdate><enddate>20240701</enddate><creator>Goncalves, Vinicius Mariano</creator><creator>Krishnamurthy, Prashanth</creator><creator>Tzes, Anthony</creator><creator>Khorrami, Farshad</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | Circulation Collision avoidance Equilibrium Lyapunov methods Motion control Navigation Optimization Potential fields Quadratic programming quadratic programming (QP) Robot control Safety |
title | Control Barrier Functions With Circulation Inequalities |
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