Spline-based Path Planning and Reconfiguration for Rigid Multi-Robot Formations

Lurz, Henrik; Recker, Tobias; Raatz, Annika

doi:10.1016/j.procir.2022.02.174

Cited by 3 publications

(7 citation statements)

References 10 publications

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“…Our approach first plans an unsmooth collision-free global path and then smoothes the curvature of the path using splines to allow nonholonomic mobile robots to traverse along the path without reversing. We previously successfully simulated the global path planning algorithm in various environments with different formations [2]. In this work, we added a formation controller as well as trajectory generation and included further experiments using two industrial mobile robots following a third virtual robot.…”

Section: Discussionmentioning

confidence: 99%

“…Choosing d s,min according to (5) allows the interpolation to connect any two points with an S-shaped spline, without exceeding κ max [2]. After choosing m control points with the distance d s,min and hence defining p 0 and p 5 , we calculate the control points p 1 and p 4 .…”

Section: B Stage 2: Formation Path Planning and Smoothingmentioning

confidence: 99%

“…The formation control is used to keep the formation on its given path and to maintain the distances between robots. The performance of this feedback controller can be improved by adding a feed-forward term ĉi 2 . In this section, we first describe the generation of the target trajectory, which is later used to compute the feed-forward term and then introduce the formation controller.…”

Section: Controlmentioning

confidence: 99%

“…In this section, we first describe the generation of the target trajectory, which is later used to compute the feed-forward term and then introduce the formation controller. 2 we denote target values with a circumflex in this paper Fig. 4.…”

Section: Controlmentioning

confidence: 99%

“…The algorithm calculates a smooth trajectory to a given target location while considering predefined velocity and acceleration limits for every mobile robot in the formation and prevents reversing. We have already developed the underlying algorithm in [2] and refer the reader to this publication for more details. The following paper adds a formation controller, an algorithm to plan synchronized trajectories for all robots, and provides additional experimental evaluation.…”

Section: Introductionmentioning

confidence: 99%

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Smooth Spline-based Trajectory Planning for Semi-Rigid Multi-Robot Formations

Recker¹,

Lurz²,

Raatz³

2022

2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)

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This paper presents an approach for smooth trajectory planning in semi-rigid nonholonomic mobile robot formations using Beziér-splines. Unlike most existing approaches, the focus is on maintaining a semi-rigid formation, as required in many scenarios such as object transport, handling or assembly. We use a Relaxed A* planner to create an optimal collisionfree global path and then smooth this path using splines. The smoothed global path serves to create target paths for every robot in the formation. From these paths, we then calculate the trajectories for each robot. In an iterative process, we match the velocities of the robots so that all trajectories are synchronized, and the dynamic limits of all robots are maintained. We provide experimental validation, which confirms no violation of the dynamic limits and shows an excellent control performance for a system of three robots moving at 0.3 m/s.

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Section: Discussionmentioning

confidence: 99%

Section: B Stage 2: Formation Path Planning and Smoothingmentioning

confidence: 99%

Section: Controlmentioning

confidence: 99%

Section: Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Smooth Spline-based Trajectory Planning for Semi-Rigid Multi-Robot Formations

Recker¹,

Lurz²,

Raatz³

2022

2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)

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On the Intersection of Computational Geometry Algorithms with Mobile Robot Path Planning

Latif,

Parasuraman

2023

Algorithms

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In the mathematical discipline of computational geometry (CG), practical algorithms for resolving geometric input and output issues are designed, analyzed, and put into practice. It is sometimes used to refer to pattern recognition and to define the solid modeling methods for manipulating curves and surfaces. CG is a rich field encompassing theories to solve complex optimization problems, such as path planning for mobile robot systems and extension to distributed multi-robot systems. This brief review discusses the fundamentals of CG and its application in solving well-known automated path-planning problems in single- and multi-robot systems. We also discuss three winning algorithms from the CG-SHOP (Computational Geometry: Solving Hard Optimization Problems) 2021 competition to evidence the practicality of CG in multi-robotic systems. We also mention some open problems at the intersection of CG and robotics. This review provides insights into the potential use of CG in robotics and future research directions at their intersection.

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A Review of Path-Planning Approaches for Multiple Mobile Robots

Lin

Liu²,

Wang³

et al. 2022

Machines

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Numerous path-planning studies have been conducted in past decades due to the challenges of obtaining optimal solutions. This paper reviews multi-robot path-planning approaches and decision-making strategies and presents the path-planning algorithms for various types of robots, including aerial, ground, and underwater robots. The multi-robot path-planning approaches have been classified as classical approaches, heuristic algorithms, bio-inspired techniques, and artificial intelligence approaches. Bio-inspired techniques are the most employed approaches, and artificial intelligence approaches have gained more attention recently. The decision-making strategies mainly consist of centralized and decentralized approaches. The trend of the decision-making system is to move towards a decentralized planner. Finally, the new challenge in multi-robot path planning is proposed as fault tolerance, which is important for real-time operations.

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Spline-based Path Planning and Reconfiguration for Rigid Multi-Robot Formations

Cited by 3 publications

References 10 publications

Smooth Spline-based Trajectory Planning for Semi-Rigid Multi-Robot Formations

Smooth Spline-based Trajectory Planning for Semi-Rigid Multi-Robot Formations

On the Intersection of Computational Geometry Algorithms with Mobile Robot Path Planning

A Review of Path-Planning Approaches for Multiple Mobile Robots

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