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A Distributed Layered Planning and Control Algorithm for Teams of Quadrupedal Robots: An Obstacle-Aware Nonlinear Model Predictive Control Approach.

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Title: A Distributed Layered Planning and Control Algorithm for Teams of Quadrupedal Robots: An Obstacle-Aware Nonlinear Model Predictive Control Approach.
Authors: Imran, Basit Muhammad1 basit@vt.edu, Fawcett, Randall T.1 randallf@vt.edu, Jeeseop Kim2 jeeseop@caltech.edu, Leonessa, Alexander1 aleoness@vt.edu, Hamed, Kaveh Akbari1 kavehakbarihamed@vt.edu
Source: Journal of Dynamic Systems, Measurement, & Control. May2025, Vol. 147 Issue 3, p1-16. 16p.
Subjects: Real-time control, Prediction models, Pendulums, Algorithms, A priori
Abstract: This paper aims to develop a distributed layered control framework for the navigation, planning, and control of multi-agent quadrupedal robots subject to environments with uncertain obstacles and various disturbances. At the highest layer of the proposed layered control, a reference path for all agents is calculated, considering artificial potential fields (APF) under a priori known obstacles. Second, in the middle layer, we employ a distributed nonlinear model predictive control (NMPC) scheme with a one-step delay communication protocol (OSDCP) subject to reduced-order and linear inverted pendulum (LIP) models of agents to ensure the feasibility of the gaits and collision avoidance, addressing the degree of uncertainty in real-time. Finally, low-level nonlinear whole-body controllers (WBCs) impose the full-order locomotion models of agents to track the optimal and reduced-order trajectories. The proposed controller is validated for effectiveness and robustness on up to four A1 quadrupedal robots in simulations and two robots in the experiments.1 Simulations and experimental validations demonstrate that the proposed approach can effectively address the real-time planning and control problem. In particular, multiple A1 robots are shown to navigate various environments, maintaining collision-free distances while being subject to unknown external disturbances such as pushes and rough terrain. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Dynamic Systems, Measurement, & Control is the property of American Society of Mechanical Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 184740585
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Label: Title
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  Data: A Distributed Layered Planning and Control Algorithm for Teams of Quadrupedal Robots: An Obstacle-Aware Nonlinear Model Predictive Control Approach.
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  Data: <searchLink fieldCode="AR" term="%22Imran%2C+Basit+Muhammad%22">Imran, Basit Muhammad</searchLink><relatesTo>1</relatesTo><i> basit@vt.edu</i><br /><searchLink fieldCode="AR" term="%22Fawcett%2C+Randall+T%2E%22">Fawcett, Randall T.</searchLink><relatesTo>1</relatesTo><i> randallf@vt.edu</i><br /><searchLink fieldCode="AR" term="%22Jeeseop+Kim%22">Jeeseop Kim</searchLink><relatesTo>2</relatesTo><i> jeeseop@caltech.edu</i><br /><searchLink fieldCode="AR" term="%22Leonessa%2C+Alexander%22">Leonessa, Alexander</searchLink><relatesTo>1</relatesTo><i> aleoness@vt.edu</i><br /><searchLink fieldCode="AR" term="%22Hamed%2C+Kaveh+Akbari%22">Hamed, Kaveh Akbari</searchLink><relatesTo>1</relatesTo><i> kavehakbarihamed@vt.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Dynamic+Systems%2C+Measurement%2C+%26+Control%22">Journal of Dynamic Systems, Measurement, & Control</searchLink>. May2025, Vol. 147 Issue 3, p1-16. 16p.
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  Data: <searchLink fieldCode="DE" term="%22Real-time+control%22">Real-time control</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink><br /><searchLink fieldCode="DE" term="%22Pendulums%22">Pendulums</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22A+priori%22">A priori</searchLink>
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  Label: Abstract
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  Data: This paper aims to develop a distributed layered control framework for the navigation, planning, and control of multi-agent quadrupedal robots subject to environments with uncertain obstacles and various disturbances. At the highest layer of the proposed layered control, a reference path for all agents is calculated, considering artificial potential fields (APF) under a priori known obstacles. Second, in the middle layer, we employ a distributed nonlinear model predictive control (NMPC) scheme with a one-step delay communication protocol (OSDCP) subject to reduced-order and linear inverted pendulum (LIP) models of agents to ensure the feasibility of the gaits and collision avoidance, addressing the degree of uncertainty in real-time. Finally, low-level nonlinear whole-body controllers (WBCs) impose the full-order locomotion models of agents to track the optimal and reduced-order trajectories. The proposed controller is validated for effectiveness and robustness on up to four A1 quadrupedal robots in simulations and two robots in the experiments.1 Simulations and experimental validations demonstrate that the proposed approach can effectively address the real-time planning and control problem. In particular, multiple A1 robots are shown to navigate various environments, maintaining collision-free distances while being subject to unknown external disturbances such as pushes and rough terrain. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Dynamic Systems, Measurement, & Control is the property of American Society of Mechanical Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1115/1.4066632
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      – Code: eng
        Text: English
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        PageCount: 16
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      – SubjectFull: Real-time control
        Type: general
      – SubjectFull: Prediction models
        Type: general
      – SubjectFull: Pendulums
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: A priori
        Type: general
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      – TitleFull: A Distributed Layered Planning and Control Algorithm for Teams of Quadrupedal Robots: An Obstacle-Aware Nonlinear Model Predictive Control Approach.
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            NameFull: Imran, Basit Muhammad
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            NameFull: Fawcett, Randall T.
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            NameFull: Jeeseop Kim
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            NameFull: Leonessa, Alexander
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            NameFull: Hamed, Kaveh Akbari
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            – D: 01
              M: 05
              Text: May2025
              Type: published
              Y: 2025
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              Value: 147
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            – TitleFull: Journal of Dynamic Systems, Measurement, & Control
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