Navigation of Three Cooperative Object-Transportation Robots Using a Multistage Evolutionary Fuzzy Control Approach

Juang, Chia‐Feng; Lu, Chiahao; Huang, Chen-An

doi:10.1109/tcyb.2020.3015960

Cited by 14 publications

(1 citation statement)

References 49 publications

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“…When dealing with more complex tasks, the functions and capabilities of a single robot are limited. Multi-robots gradually replace the single robot to achieve more complex work [17]. In our luggage trolley transport task, the connection between any adjacent two trolleys is not perfectly rigid, so the connection is unstable.…”

Section: Related Workmentioning

confidence: 99%

A divide-and-conquer control strategy with decentralized control barrier function for luggage trolley transportation by collaborative robots

Gao,

Luan,

Xia

et al. 2023

Robotica

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This article focuses on the luggage trolley transportation problem, an essential part of robotic autonomous luggage trolley collection. To efficiently address the nonholonomic constraints derived from the formation of two collaborative robots and a queue of luggage trolleys, we propose a comprehensive framework consisting of a global planning method and a real-time divide-and-conquer control strategy. The popular Hybrid A* algorithm generates a feasible path as the global planner. A model predictive controller is designed to track this path stably and in real time. To maintain the formation so that the whole queue of robots and luggage trolleys does not split, a safety filter that consists of a discrete-time control Lyapunov function and a decentralized control barrier function is implemented in the transportation process. Finally, we conduct real-world experiments to verify the effectiveness of the proposed method on three representative paths, and the results show that our approach can achieve robust performance. The demonstration video can be found at https://www.youtube.com/watch?v=iPiT8BfLIpU.

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Section: Related Workmentioning

confidence: 99%

A divide-and-conquer control strategy with decentralized control barrier function for luggage trolley transportation by collaborative robots

Gao,

Luan,

Xia

et al. 2023

Robotica

View full text Add to dashboard Cite

show abstract

Autonomous learning for fuzzy systems: a review

Han

Shen

et al. 2022

Artif Intell Rev

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As one of the three pillars in computational intelligence, fuzzy systems are a powerful mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy systems take the form of linguistic IF-THEN fuzzy rules that are easy to understand for human. In this sense, fuzzy inference mechanisms have been developed to mimic human reasoning and decision-making. From a data analytic perspective, fuzzy systems provide an effective solution to build precise predictive models from imprecise data with great transparency and interpretability, thus facilitating a wide range of real-world applications. This paper presents a systematic review of modern methods for autonomously learning fuzzy systems from data, with an emphasis on the structure and parameter learning schemes of mainstream evolving, evolutionary, reinforcement learning-based fuzzy systems. The main purpose of this paper is to introduce the underlying concepts, underpinning methodologies, as well as outstanding performances of the state-of-the-art methods. It serves as a one-stop guide for readers learning the representative methodologies and foundations of fuzzy systems or who desire to apply fuzzy-based autonomous learning in other scientific disciplines and applied fields.

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Neural admittance control based on motion intention estimation and force feedforward compensation for human–robot collaboration

Ai,

Pan,

Jiang

et al. 2024

Int J Intell Robot Appl

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Navigation of Three Cooperative Object-Transportation Robots Using a Multistage Evolutionary Fuzzy Control Approach

Cited by 14 publications

References 49 publications

A divide-and-conquer control strategy with decentralized control barrier function for luggage trolley transportation by collaborative robots

A divide-and-conquer control strategy with decentralized control barrier function for luggage trolley transportation by collaborative robots

Autonomous learning for fuzzy systems: a review

Neural admittance control based on motion intention estimation and force feedforward compensation for human–robot collaboration

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