A trajectory reconstruction approach for leader-following of multi-robot system

Zou, Ying; Shan, Mao; Guan, Mingyang; Chen, Wen; Lim, K.P.

doi:10.1109/iciea.2017.8283082

Cited by 1 publication

(6 citation statements)

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“…The authors apply a particle filter, utilizing observations from a vision sensor and the odometry data of the follower/leader pair, to estimate the leader's trajectory. A simple trajectory-reconstruction approach is presented in [8], basically implementing a first-in-first-out buffer where the oldest measurement is removed from the list of measurements before the current measurement is added. Unfortunately, both works [7,8] only present results obtained from simulations lacking experimental data.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A simple trajectory-reconstruction approach is presented in [8], basically implementing a first-in-first-out buffer where the oldest measurement is removed from the list of measurements before the current measurement is added. Unfortunately, both works [7,8] only present results obtained from simulations lacking experimental data.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In contrast to the works discussed above, the process to obtain the leader path is presented in quite a lot of detail. The stored leader measurements are maintained based on a first-in-first-out method similar to [8].…”

Section: Literature Reviewmentioning

confidence: 99%

“…• They rely on V2V communication [12][13][14][15][16] or GPS [6]. • They lack experimental results [7,8,[13][14][15]]. • They focus on the design of a camera system for leader tracking [2], handling intermittent vision observations [7], or state-estimation techniques [16].…”

Section: Literature Reviewmentioning

confidence: 99%

“…In this respect, the most relevant existing works are [8,9,12] regarding contribution (1) and [9,10] regarding contribution (2).…”

Section: Literature Reviewmentioning

confidence: 99%

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Leader-Based Trajectory Following in Unstructured Environments—From Concept to Real-World Implementation

2022

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In this paper, the problem of vehicle guidance by means of an external leader is described. The objective is to navigate a four-wheeled vehicle through unstructured environments, characterized by the lack of availability of typical guidance infrastructure like lane markings or HD maps. The trajectory-following approach is based on an estimate of the leader’s path. For that, position measurements are stored over time with respect to an inertial frame. A new strategy is proposed to rate the significance of position measurements and ensure that a certain threshold of stored samples is not exceeded. Having an estimate of the leader path is essential to prevent the cutting-corner phenomenon and for exact path following in general. A spline-approximation technique is applied to obtain a smooth reference path for the underlying lateral and longitudinal motion controllers. For longitudinal tracking, a constant time-headway policy was implemented, to follow the leader with a constant time gap along the estimated path. The algorithm was first developed and tested in a simulation framework and then deployed in a demonstrator vehicle for validation under real operating conditions. The presented experimental results were achieved using only on-board sensors of the demonstrator vehicle, while high-accuracy differential GPS-based position measurements serve as the ground truth data for visualization.

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Section: Literature Reviewmentioning

confidence: 99%