2021 3rd Novel Intelligent and Leading Emerging Sciences Conference (NILES) 2021
DOI: 10.1109/niles53778.2021.9600510
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LbCS navigation controllers of Twining Lagrangian swarm individuals

Abstract: This paper presents stabilizing velocity controllers for the individuals of two Lagrangian swarms, which navigates from their initial configuration space to their final configuration space, ensuring intra and inter swarm individual collision avoidance. The motion of the individuals is based on Reynold's rules of separation, alignment, and cohesion. Using the three pillars (safety, shortest and smoothest path) of Lyapunov based control scheme (LbCS), the velocity controllers of the individuals of the two swarms… Show more

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Cited by 9 publications
(5 citation statements)
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References 30 publications
(14 reference statements)
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“…The proposed system has higher flexibility as it can move easily along the rail to perform assigned tasks. Its increased mobility offers better use of space and has the ability to contribute towards high productivity when compared to the anchored manipulators presented in [13] and [18] . The linear manipulator system presented in this study is a modification of existing robotic arms due to its ability to reposition and navigate to distant targets, resulting from a change in work requirements.…”
Section: Discussionmentioning
confidence: 99%
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“…The proposed system has higher flexibility as it can move easily along the rail to perform assigned tasks. Its increased mobility offers better use of space and has the ability to contribute towards high productivity when compared to the anchored manipulators presented in [13] and [18] . The linear manipulator system presented in this study is a modification of existing robotic arms due to its ability to reposition and navigate to distant targets, resulting from a change in work requirements.…”
Section: Discussionmentioning
confidence: 99%
“…The ruling principle behind the potential method is to assign a repulsive field to each obstacle and an attractive field to the target [15] , [53] . The Lyapunov function is the sum of each and every repulsive and attractive potential functions [54] , [48] , thus establishing a basis for deriving the controllers of a linear manipulator. The repulsive potential function is a ratio of a positive tuning parameter to the obstacle avoidance function.…”
Section: Lyapunov-based Control Schemementioning
confidence: 99%
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“… Sharma, Vanualailai & Prasad (2017) proposed the Lyapunov-based Control Scheme (LbCS), which falls under the artificial potential field method, widely used in robotics research for motion planning and control of robotic systems. The time-invariant nonlinear velocity or acceleration controllers can be derived from LbCS, which has been successfully applied in the literature to find feasible and stabilizing solutions to a variety of problems ( Sharma, Vanualailai & Singh, 2015 ; Sharma, Vanualailai & Singh, 2014 ; Kumar, Vanualailai & Sharma, 2016 ; Chand, Kumar & Chand, 2021 ; Sharma et al, 2018 ; Kumar et al, 2021 ; Sharma, Raj & Vanualailai, 2018 ).…”
Section: Lyapunov-based Control Schemementioning
confidence: 99%