MeWBots: Mecanum-Wheeled Robots for Collaborative Manipulation in an Obstacle-Clustered Environment Without Communication

Rauniyar, Aditya; Upreti, Hem Chandra; Mishra, Aman Kumar; Sethuramalingam, Prabhu

doi:10.1007/s10846-021-01359-5

Cited by 9 publications

(3 citation statements)

References 30 publications

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“…More centralised state machines have also been proposed. A leaderfollower strategy includes multiple robots pushing a box while following the trajectory of an (often human-controlled) 'leader' robot towards the goal (Brown & Jennings, 1995;Kosuge & Oosumi, 1996;Rauniyar, Upreti, Mishra, & Sethuramalingam, 2021;Takeda, Hirata, Wang, & Kosuge, 2002;Z. Wang & Schwager, 2016).…”

Section: Related Workmentioning

confidence: 99%

“…While certain presuppositions and requirements seem to be an inescapable feature of many multi-robot object transportation strategies, in this study, we examine the issue of complex environments where objects are present that may block the straightline path between the object and the goal. Existing strategies able to overcome this challenge often make use of a leader-follower approach (Rauniyar et al, 2021), wherein the leader traces a path around the obstacles. However, this comes with the assumption that the leader possesses knowledge of the global environment, or that the leader is human-controlled.…”

Section: Related Workmentioning

confidence: 99%

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Occlusion-Based Object Transportation Around Obstacles With a Swarm of Miniature Robots

Queiroz,

MacRae

2024

Preprint

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Swarm robotics utilises decentralised self-organising systems to form complex collective behaviours built from the bottom-up using individuals that have limited capabilities. Previous work has shown that simple occlusion-based strategies can be effective in using swam robotics for the task of transporting objects to a goal position. However, this strategy requires a clear line-of-sight between object and goal. In this paper, we extend this strategy by allowing robots to form sub-goals; enabling any member of the swarm to establish a wider range of visibility of the goal, ultimately forming a chain of sub-goals between the object and the goal position. We do so while maintaining the fully decentralised and communication-free nature of the original strategy. In three sets of simulated experiments, we demonstrate that our proposed approach allows a swarm of sufficient size to successfully transport objects around obstacles that occlude the goal from the starting position of the object, that this strategy is robust to different object shapes, and that our proposed changes do not reduce the performance of the strategy in environments where obstacles are not present.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Occlusion-Based Object Transportation Around Obstacles With a Swarm of Miniature Robots

Queiroz,

MacRae

2024

Preprint

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“…Compared with wheeled mobile robots with incomplete characteristics, Mecanum wheel trolley has higher mobility and flexibility [12] . Figure 1 describes the motion diagram of a single Mecanum four-wheel robot car in the global coordinate system.…”

Section: Mathematical Model Of Multi-robot Formation Errormentioning

confidence: 99%

Multi-robot formation control based on backstepping and improved potential field RRT

Yan,

Tang,

et al. 2024

Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024)

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To solve the problem of formation and cooperative obstacle avoidance of multi-wheeled robots in the environment with obstacles, an algorithm combining the leader-follower and improved potential field with rapidly exploring random trees(IPFRRT) is proposed in this paper. The kinematic model of multiple robots is established, and the control rate of the path following of the following robots is designed by the backsteeping according to the error differential equation, and the stable formation of the robots is realized. At the same time, the IPFRRT is used as the path planning method for the leader, and the improved artificial potential field method is used as the local obstacle avoidance algorithm for the followers in the formation, so that the multi-robot system can simultaneously avoid obstacles in the formation. The Matlab simulation experiment shows that the robot system can quickly form and maintain formation, continue to recover formation after avoiding obstacles, and make the following error tend to 0 after avoiding obstacles, which verifies the feasibility of the formation control method.

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Four Wheeled Humanoid Second-Order Cascade Control of Holonomic Trajectories

Torres-Martínez,

Martínez-García,

Lavrenov

et al. 2023

Studies in Computational Intelligence

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MeWBots: Mecanum-Wheeled Robots for Collaborative Manipulation in an Obstacle-Clustered Environment Without Communication

Cited by 9 publications

References 30 publications

Occlusion-Based Object Transportation Around Obstacles With a Swarm of Miniature Robots

Occlusion-Based Object Transportation Around Obstacles With a Swarm of Miniature Robots

Multi-robot formation control based on backstepping and improved potential field RRT

Four Wheeled Humanoid Second-Order Cascade Control of Holonomic Trajectories

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