4.6 Article

Adaptive Finite-Time Tracking Control of Nonholonomic Multirobot Formation Systems With Limited Field-of-View Sensors

Journal

IEEE TRANSACTIONS ON CYBERNETICS
Volume 52, Issue 10, Pages 10695-10708

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2021.3063481

Keywords

Robot sensing systems; Transient analysis; Mobile robots; Steady-state; Sensors; Collision avoidance; Wheels; Adaptive control; barrier Lyapunov function; collision avoidance; finite-time formation control; visibility constraints

Funding

  1. National Natural Science Foundation of China [61973129, 62073090, 61825301]
  2. National Key Research and Development Program of China [2018AAA0101603]
  3. Guangdong Natural Science Foundation [2019B151502058]
  4. KeyArea Research and Development Program of Guangdong Province [2020B1111010002]
  5. Guangdong Marine Economic Development Project [GDNRC [2020]018]
  6. Fundamental Research Funds for the Central Universities

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This article studies the vision-based tracking control problem for a nonholonomic multirobot formation system with uncertain dynamic models and visibility constraints. A decentralized control protocol is proposed, incorporating barrier Lyapunov function to address constraint problems and achieving formation tracking errors that meet the requirements of visibility and performance constraints. Both simulation and experimental results demonstrate the effectiveness of the control protocol.
This article studies the vision-based tracking control problem for a nonholonomic multirobot formation system with uncertain dynamic models and visibility constraints. A fixed onboard vision sensor that provides the relative distance and bearing angle is subject to limited range and angle of view due to limited sensing capability. The constraint resulting from collision avoidance is also taken into account for safe operations of the formation system. Furthermore, the preselected specifications on transient and steady-state performance are provided by considering the time-varying and asymmetric constraint requirements on formation tracking errors for each robot. To address the constraint problems, we incorporate a novel barrier Lyapunov function into controller design and analysis. Based on the recursive adaptive backstepping procedure and neural-network approximation, we develop a vision-based formation tracking control protocol such that formation tracking errors can converge into a small neighborhood of the origin in finite time while meeting the requirements of visibility and performance constraints. The proposed protocol is decentralized in the sense that the control action on each robot only depends on the local relative information, without the need for explicit network communication. Moreover, the control protocol could extend to an unconstrained multirobot system. Both simulation and experimental results show the effectiveness of the control protocol.

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