Design and development of novel control strategy for trajectory tracking of mobile robot: Featured with tracking error minimization

Anushree, R.; Prasad, Bhuneshwar

doi:10.1109/indicon.2016.7839162

Cited by 7 publications

(1 citation statement)

References 10 publications

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“…5) Experiments and simulations are conducted to validate the theoretical developments. Both the simulations and experiments are conducted using different initial conditions which have not been done in previous works (see for example [10], [12], [13], [16], [17], [19]- [21], [23], [23], [25]- [33], [35], [36]). The rest of the paper is arranged as follows: In Section 2, the system description, modelling, and problem formulation are given.…”

Section: Introductionmentioning

confidence: 99%

LiDAR Based Trajectory-Tracking of an Autonomous Differential Drive Mobile Robot Using Fuzzy Sliding Mode Controller

Zaman

2022

IEEE Access

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This study aims to achieve the trajectory-tracking of an autonomous differential drive mobile robot (ADDMR) in the presence of friction torques using the proposed Fuzzy Sliding-Mode Control (FSMC). First, the complete model of the ADDMR is established including kinematic, dynamic and actuator models. Then, the desired trajectory is planned and generated via Bézier curve combined with cubic time mapping. The localization of the ADDMR is performed using the Monte Carlo Localization (MCL) technique and LiDAR point cloud data. Subsequently, the proposed FSMC utilizes nonlinear sliding surfaces inferred based on fuzzy logic to asymptotically attain the pose convergence. To investigate the feasibility and robustness of the proposed FSMC, simulations and experiments are conducted under different operation conditions. The results show that the proposed FSMC using LiDAR data in the feedback leads to excellent control performance even in the presence of friction torques. It was also shown through simulations and experiments that the established ADDMR model fits the actual ADDMR model very well.

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