A decoupling three-dimensional motion control algorithm for spherical underwater robot

Bao, Pengxiao; Hu, Yao; Shi, Liwei; Guo, Shuxiang; Li, Zhengyu

doi:10.1016/j.birob.2022.100067

Cited by 3 publications

(5 citation statements)

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“…References [2,5,7] showed that by adopting vectored water-jets, a spherical UUV can maneuver freely in any direction. The control of a spherical UUV was addressed in [8]. The authors of [8] proposed a decoupling motion control based on the attitude calculation for an underwater spherical robot.…”

Section: Assumptions and Definitionsmentioning

confidence: 99%

“…The control of a spherical UUV was addressed in [8]. The authors of [8] proposed a decoupling motion control based on the attitude calculation for an underwater spherical robot. The authors of [8] utilized fuzzy PID controllers to independently control the robot's movement in all directions.…”

Section: Assumptions and Definitionsmentioning

confidence: 99%

“…The authors of [8] proposed a decoupling motion control based on the attitude calculation for an underwater spherical robot. The authors of [8] utilized fuzzy PID controllers to independently control the robot's movement in all directions. Since a spherical UUV is highly maneuverable, the process model in ( 1) is feasible.…”

Section: Assumptions and Definitionsmentioning

confidence: 99%

“…Considering a spherical UUV, ref. [8] utilized fuzzy proportional-integral-derivative (PID) controls to independently control the robot's maneuver in all directions. Since spherical UUVs are highly maneuverable, our article considers a spherical UUV [2][3][4][5][6] as our robot platform.…”

Section: Introductionmentioning

confidence: 99%

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Leader-Based Flocking of Multiple Swarm Robots in Underwater Environments

Kim

2023

Sensors

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Considering underwater environments, this paper tackles flocking of multiple swarm robots utilizing one leader. The mission of swarm robots is to reach their goal while not colliding with a priori unknown 3D obstacles. In addition, the communication link among the robots needs to be preserved during the maneuver. Only the leader has sensors for localizing itself while accessing the global goal position. Every robot, except for the leader, can measure the relative position and the ID of its neighboring robots by utilizing proximity sensors such as Ultra-Short BaseLine acoustic positioning (USBL) sensors. Under the proposed flocking controls, multiple robots flock inside a 3D virtual sphere while preserving communication connectivity with the leader. If necessary, all robots rendezvous at the leader to increase connectivity among the robots. The leader herds all robots to reach the goal safely, while the network connectivity is maintained in cluttered underwater environments. To the best of our knowledge, our article is novel in developing underwater flocking controls utilizing one leader, so that a swarm of robots can safely flock to the goal in a priori unknown cluttered environments. MATLAB simulations were utilized to validate the proposed flocking controls in underwater environments with many obstacles.

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Section: Assumptions and Definitionsmentioning

confidence: 99%

Section: Assumptions and Definitionsmentioning

confidence: 99%

Section: Assumptions and Definitionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Leader-Based Flocking of Multiple Swarm Robots in Underwater Environments

Kim

2023

Sensors

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“…Along the generated path, each end point of a straight line is set as the waypoint for an agent. With the waypoints set, we can utilize the path following controller in [38,39] while considering the dynamics of the agent to ensure that an agent visits the waypoints. How to ensure that an agent with motion constraints move along the waypoints is beyond the scope of the present paper.…”

Section: Assumptions and Notationmentioning

confidence: 99%

Three-Dimensional Multi-Agent Foraging Strategy Based on Local Interaction

Kim

2023

Sensors

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In this paper, we consider a multi-agent foraging problem in which multiple autonomous agents find resources (called pucks) in a bounded workspace and carry the found resources to a designated location called the base. We consider the case where autonomous agents move in unknown 3D workspace with many obstacles. This article describes 3D multi-agent foraging based on local interaction, which does not rely on global localization of an agent. We propose a 3D foraging strategy with the following two steps. The first step is to detect all pucks inside the 3D cluttered unknown workspace such that every puck in the workspace is detected in a provably complete manner. The next step is to generate a path from the base to every puck, collect every puck, and return them to the base. Because an agent cannot use global localization, each agent depends on local interaction to bring every puck to the base. In this article, every agent on a path to a puck is used in guiding an agent to reach the puck and to bring it to the base. To the best of our knowledge, this article is novel in letting multiple agents perform foraging and puck-carrying in 3D cluttered unknown workspace while not relying on global localization of an agent. In addition, the proposed search strategy is provably complete in detecting all pucks in the 3D cluttered bounded workspace. MATLAB simulations demonstrate that the proposed multi-agent foraging strategy outperforms alternatives in a 3D cluttered workspace.

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