Consensus-Based Artificial Potential Field Approach for Swarm

Machida, Manao; Ichien, Masumi

doi:10.1109/cdc45484.2021.9683380

Cited by 2 publications

(3 citation statements)

References 26 publications

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“…In [12], an APF-based consensus control method is presented to formulate coordination and control strategies between robots without considering avoiding obstacles. An improved APF is proposed in [13] for path planning of a multirobot formation which efficiently avoids getting trapped in local minima caused by obstacles but fails to address deadlocks among robots reaching their goal positions.…”

Section: Related Workmentioning

confidence: 99%

“…For each robot, we use first-order consensus control to maintain the formation. Similar to (4), the control input for the ith follower of the jth formation at time t is given by: (12) where x ctr j is the state of the virtual leader, u(x ctr j ) is the virtual leader's control input, and there are k robots in the formation.…”

Section: B Consensus-based Trajectory Trackingmentioning

confidence: 99%

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Multi-Formation Planning and Coordination for Object Transportation

Zhang,

Street,

Mansouri

2023

2023 European Conference on Mobile Robots (ECMR)

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Multi-robot formations have numerous applications, such as cooperative object transportation in smart warehouses. Here, robots must deliver objects in formation while avoiding intra-and inter-formation collisions. This requires solutions to multi-robot task assignment, formation generation, rigid formation maintenance, and route planning. In this paper, we present a cooperative multi-formation object transportation system which explicitly handles inter-formation collisions. For formation generation, we propose a distributed motion planning approach which combines artificial potential field methods and leader-follower based control. For formation planning, we present a heuristic search-based algorithm which uses convex segmentation techniques, and extend the minimum snap method to synthesise smooth trajectories while maintaining the formation. We also propose a variant of the dynamic window approach to avoid collisions between formations. We demonstrate the efficacy of our approach in simulation.

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Section: Related Workmentioning

confidence: 99%

Section: B Consensus-based Trajectory Trackingmentioning

confidence: 99%

Multi-Formation Planning and Coordination for Object Transportation

Zhang,

Street,

Mansouri

2023

2023 European Conference on Mobile Robots (ECMR)

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“…In Muslimov and Munasypov (2021), the fuzzy logic-based model reference adaptive control was used to achieve consensus between UAVs for tracking a mobile ground target. An alternate approach using artificial potential field (APF)-based consensus control was used in Machida and Ichien (2021) to formulate coordinate and control strategies between agents in MAS. Using SMC and APF, a robust consensus controller was proposed by Gazi (2005) for swarm aggregate.…”

Section: Introductionmentioning

confidence: 99%

Adaptive sliding mode controller based consensus protocol for swarm of UAVs

Dixit

Agrawal

Misra

2022

AEAT

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Purpose The requirement of robust cooperative control is essential to achieve consensus between unmanned aerial vehicles (UAVs) operating in swarm formation. Often the performance of these swarm formations is affected by wind gust disturbances. This study proposes an effective robust consensus protocol, which will ensure the UAVs in swam formation to collectively meet the desired objective in real-time scenario. Design/methodology/approach In this work, the swarm of UAVs are modeled as multiagent systems by using the concepts of algebraic graph theory. To address the challenges of a complex and dynamic environment, an adaptive sliding mode control (SMC)-based consensus protocol is proposed. The closed loop stability analysis is established through Lyapunov theory. Findings The efficacy of the discussed robust consensus controller is analyzed through numerical simulations. Further, the quantitative analysis using Monte-Carlo simulations validates performance of the proposed robust consensus protocol. The presented consensus protocol can be easily implementable as robust flight controller for swarm of UAVs. Also, as the consensus theory is based on the algebraic graph theory, the proposed design is scalable for a large number of UAVs in swarm formation. Originality/value The proposed adaptive SMC achieves robust consensus of longitudinal dynamics states between all the UAVs by mitigating the effects of wind gust disturbances. Also, the adaptive SMC offers chattering-free control efforts.

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Consensus-Based Artificial Potential Field Approach for Swarm

Cited by 2 publications

References 26 publications

Multi-Formation Planning and Coordination for Object Transportation

Multi-Formation Planning and Coordination for Object Transportation

Adaptive sliding mode controller based consensus protocol for swarm of UAVs

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