A Comparison of Different Approaches for Formation Control of Nonholonomic Mobile Robots regarding Object Transport

Recker, Tobias; Heinrich, Malte; Raatz, Annika

doi:10.1016/j.procir.2021.01.082

Cited by 14 publications

(6 citation statements)

References 9 publications

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“…More importantly, the measurements show no visible impact of the angular velocity/acceleration on the linear error for a smoothed trajectory in great contrast to previous measurements using unsmooth trajectories [10]. For this reason, a significantly higher formation speed can be achieved without reducing the formation control quality at the same time.…”

Section: Discussionmentioning

confidence: 57%

“…At the same time, these constraints also mean that the outer robots in a formation are subject to high velocities and accelerations whenever the formation changes its orientation. This strong excitation of the formation controller has a detrimental effect on the control performance and occurs increasingly with unsmooth formation paths [10]. For this reason, [11] developed an approach that bridges the aforementioned gap between path planning and formation control while also generating smooth trajectories.…”

Section: Related Workmentioning

confidence: 99%

“…A more detailed description and evaluation of the presented controller can be found in [10] and [19].…”

Section: B Formation Controllermentioning

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: 57%

Section: Related Workmentioning

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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“…Wheeled mobile robots have been one of the most studied robotic platforms due to their applicability and motion capabilities. In the field of multi-agent systems (MAS), control schemes for collaborative wheeled robots have been developed for environmental sensing [ 1 ], task allocation for search and rescue [ 2 ], coverage control for precision agriculture [ 3 ] and object transportation [ 4 ], among others. For such applications, different control protocols have been reported in the literature, using centralized methods that depend on a global coordinate system as a first attempt, e.g., [ 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Formation Tracking Control and Obstacle Avoidance of Unicycle-Type Robots Guaranteeing Continuous Velocities

Martínez

Becerra

Gómez‐Gutiérrez

2021

Sensors

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In this paper, we addressed the problem of controlling the position of a group of unicycle-type robots to follow in formation a time-varying reference avoiding obstacles when needed. We propose a kinematic control scheme that, unlike existing methods, is able to simultaneously solve the both tasks involved in the problem, effectively combining control laws devoted to achieve formation tracking and obstacle avoidance. The main contributions of the paper are twofold: first, the advantages of the proposed approach are not all integrated in existing schemes, ours is fully distributed since the formulation is based on consensus including the leader as part of the formation, scalable for a large number of robots, generic to define a desired formation, and it does not require a global coordinate system or a map of the environment. Second, to the authors’ knowledge, it is the first time that a distributed formation tracking control is combined with obstacle avoidance to solve both tasks simultaneously using a hierarchical scheme, thus guaranteeing continuous robots velocities in spite of activation/deactivation of the obstacle avoidance task, and stability is proven even in the transition of tasks. The effectiveness of the approach is shown through simulations and experiments with real robots.

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“…In another publication Recker et al[17] we have already investigated the theoretical accuracy of our formation control and developed mechanical compensation units to compensate for the lateral errors within the formation. Due to the mechanical design of the compensation units, they can only compensate errors of individual robots up to 100 mm.…”

mentioning

confidence: 99%

LiDAR-Based Localization for Formation Control of Multi-Robot Systems

Recker

Zhou

Stüde

et al. 2022

Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2021

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Controlling the formation of several mobile robots allows for the connection of these robots to a larger virtual unit. This enables the group of mobile robots to carry out tasks that a single robot could not perform. In order to control all robots like a unit, a formation controller is required, the accuracy of which determines the performance of the group. As shown in various publications and our previous work, the accuracy and control performance of this controller depends heavily on the quality of the localization of the individual robots in the formation, which itself depends on the ability of the robots to locate themselves within a map. Other errors are caused by inaccuracies in the map. To avoid any errors related to the map or external sensors, we plan to calculate the relative positions and velocities directly from the LiDAR data. To do this, we designed an algorithm which uses the LiDAR data to detect the outline of individual robots. Based on this detection, we estimate the robots pose and combine this estimate with the odometry to improve the accuracy. Lastly, we perform a qualitative evaluation of the algorithm using a Faro laser tracker in a realistic indoor environment, showing benefits in localization accuracy for environments with a low density of landmarks.

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A Comparison of Different Approaches for Formation Control of Nonholonomic Mobile Robots regarding Object Transport

Cited by 14 publications

References 9 publications

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

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

Formation Tracking Control and Obstacle Avoidance of Unicycle-Type Robots Guaranteeing Continuous Velocities

LiDAR-Based Localization for Formation Control of Multi-Robot Systems

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