Obstacle avoidance behavior of swarm robots based on aggregation and disaggregation method

Yu, Yue; Chen, Xiangru; Lu, Zhaohan; Li, Fengxia; Zhang, Bo

doi:10.1177/0037549717711281

Cited by 7 publications

(4 citation statements)

References 33 publications

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“…In recent times, the focus on robotics has shifted from the individual robot to the multirobotic systems. [19][20][21][22][23] These systems can be used for situations such as cleaning, lawn mowing, and military surveillance. 24 In such systems, large number of robots with limited capabilities coordinate with each other to accomplish a common task.…”

Section: Comparison Of Bug-1 With Other Algorithmsmentioning

confidence: 99%

Development and analysis of a novel obstacle avoidance strategy for a multi-robot system inspired by the Bug-1 algorithm

2020

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This paper addresses the development and implementation of an obstacle avoidance strategy for a multi-robot system operating in an unknown environment. This novel strategy is based on the conventional Bug-1 obstacle avoidance algorithm, which is a non-heuristic method for obstacle avoidance in an unknown environment. In the Bug-1 algorithm, a robot circumnavigates the obstacle to find the coordinates of the point, having minimum distance to the goal. In the case of the new strategy, two robots will circumnavigate the obstacle in such a manner that it will reduce both the total travel time and the distance traveled. Information acquired by the individual robots during the circumnavigation is shared across other robots to accomplish the obstacle avoidance efficiently. A theoretical analysis is carried out to show the improvement in travel time and energy expenditure of the robots in implementing the new strategy. Different test scenarios for comparing the performance of the obstacle avoidance strategies using simulations is also identified. The simulation studies using these scenarios suggest that the new algorithm is a better algorithm with respect to multi-robot obstacle avoidance. The experimental study conducted also shows that robots using this new algorithm have a better travel time and less energy expenditure than the conventional Bug-1 algorithm.

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Section: Comparison Of Bug-1 With Other Algorithmsmentioning

confidence: 99%

Development and analysis of a novel obstacle avoidance strategy for a multi-robot system inspired by the Bug-1 algorithm

2020

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“…Though LF is a simple formation control strategy, the formation keeping is not guaranteed because there is no feedback. Therefore, if a follower fails to follow properly, no mechanism can guarantee the formation keeping (Yu et al, 2017). In general, this strategy depends on the leader vehicle.…”

Section: Introductionmentioning

confidence: 99%

Leader Follower Formation Control for Underwater Transportation Using Multiple Autonomous Underwater Vehicles

Rehman¹,

Anderlini²,

Thomas³

2021

IJME

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The successful ability to conduct underwater transportation using multiple autonomous underwater vehicles (AUVs) is important for the commercial sector to undertake precise underwater installations on large modules, whilst for the military sector it has the added advantage of improved secrecy for clandestine operations. The technical requirements are the stability of the payload and internal collision avoidance while keeping track of the desired trajectory considering the underwater effects. Here, a leader-follower formation control strategy was developed and implemented on the transportation system of AUVs. PID controllers were used for the vehicles and a linear feedback controller for maintaining the formation. A Kalman Filter (KF) was designed to estimate the full state of the leader under disturbance, noise and limited sensor readings. The results demonstrate that though the technical requirements are met, the thrust oscillations under disturbance and noise produce the undesired heading angles.

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“…The main disadvantage of the current virtual structure implementation is the centralization, which leads a single point of failure for the whole system. By behavior-based approach, several desired behaviors are prescribed for each robot, and the final action of each robot is derived by weighting the relative importance of each behavior [15], [16]. The limitation of such approach, it is difficult to analyze mathematically, therefore it is hard to guarantee a precise formation control.…”

Section: Introductionmentioning

confidence: 99%

“…Several technique have proposed to give a solution with good performance [21], [5], [15], [17], [23], [24], [25], [26], [27], [28], [29]. However, in the robotic application, there are some uncertainties in the system, due to the sensors imprecision, inaccurate actuator and environment change every time [28].…”

Section: Introductionmentioning

confidence: 99%

Enhancement of Non-Holonomic Leader-Follower Formation Using Interval Type-2 Fuzzy Logic Controller

et al. 2018

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Robotics control system with leader-follower approach has a weakness in the case of formation failure if the leader robot fails. To overcome such problem, this paper proposes the formation control using Interval Type-2-Fuzzy Logic controller (IT2FLC). To validate the performance of the controller, simulations were performed with various environmental systems such as open spaces, complexes, circles and ovals with several parameters. The performance of IT2FLC will be compared with Type-1 Fuzzy Logic (T1FL) and Proportional Integral and Derivative (PID) controller. As the results found using IT2FLC has advantages in environmental uncertainty, sensor imprecision and inaccurate actuator. Moreover, IT2FLC produce good performance compared to T1FLC and PID controller in the above environments, in terms of small data generated in the fuzzy process, the rapid response of the leader robot to avoid collisions and stable movements of the follower robot to follow the leader's posture to reach the target without a crash. Especially in some situations when a leader robot crashes or stops due to hardware failure, the follower robot still continue move to the target without a collision.

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Obstacle avoidance behavior of swarm robots based on aggregation and disaggregation method

Cited by 7 publications

References 33 publications

Development and analysis of a novel obstacle avoidance strategy for a multi-robot system inspired by the Bug-1 algorithm

Development and analysis of a novel obstacle avoidance strategy for a multi-robot system inspired by the Bug-1 algorithm

Leader Follower Formation Control for Underwater Transportation Using Multiple Autonomous Underwater Vehicles

Enhancement of Non-Holonomic Leader-Follower Formation Using Interval Type-2 Fuzzy Logic Controller

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