Trajectory tracking control of a mobile robot using lidar sensor for position and orientation estimation

Lima, Thiago Alves; Forte, Marcus Davi do Nascimento; Nogueira, Fabrício G.; Torrico, Bismark C.; Paula, Adriano Rodrigues de

doi:10.1109/induscon.2016.7874573

Cited by 11 publications

(4 citation statements)

References 10 publications

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“…The piecewise-linear robot paths consist of a series of tool center positions and a series of unit orientations. Therefore, the robot path smoothing is divided into position path smoothing and orientation path smoothing (Lima et al , 2016; Niu and Tian, 2018). To improve the continuity of position paths, some methods, e.g.…”

Section: Introductionmentioning

confidence: 99%

A C2 continuous trajectory planning method for 6-DOF rotational robot manipulators

Min

Zhang

et al. 2022

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Purpose The purpose of this paper is to propose a smooth double-spline interpolation method for six-degree-of-freedom rotational robot manipulators, achieving the global C2 continuity of the robot trajectory. Design/methodology/approach This paper presents a smooth double-spline interpolation method, achieving the global C2 continuity of the robot trajectory. The tool center positions and quaternion orientations are first fitted by a cubic B-spline curve and a quartic-polynomial-based quaternion spline curve, respectively. Then, a parameter synchronization model is proposed to realize the synchronous and smooth movement of the robot along the double spline curves. Finally, an extra u-s function is used to record the relationship between the B-spline parameter and its arc length parameter, which may reduce the feed rate fluctuation in interpolation. The seven segments jerk-limited feed rate profile is used to generate motion commands for algorithm validation. Findings The simulation and experimental results demonstrate that the proposed method is effective and can generate the global C2-continuity robot trajectory. Originality/value The main contributions of this paper are as follows: guarantee the C2 continuity of the position path and quaternion orientation path simultaneously; provide a parameter synchronization model to realize the synchronous and smooth movement of the robot along the double spline curves; and add an extra u-s function to realize arc length parameterization of the B-spline path, which may reduce the feed rate fluctuation in interpolation.

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Section: Introductionmentioning

confidence: 99%

A C2 continuous trajectory planning method for 6-DOF rotational robot manipulators

Min

Zhang

et al. 2022

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“…Meanwhile, low-resolution scanners (Microsoft Kinect V2, Hokuyo and Velodyne LiDAR) are commonly used in real-time applications because they require less time for generating 3D data [3] and are suitable for 3D environment analysis. LiDAR scanners are commonly used in UAVs [4,5], robots [6] and autonomous cars [7]. Hence, laser sensor technology provides accurate geometric information by acquiring the complicated surfaces using various methods.…”

Section: Introductionmentioning

confidence: 99%

On-Site 4-in-1 Alignment: Visualization and Interactive CAD Model Retrofitting Using UAV, LiDAR’s Point Cloud Data, and Video

Kumar

Patil

Chethana

et al. 2019

Sensors

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Acquisition of 3D point cloud data (PCD) using a laser scanner and aligning it with a video frame is a new approach that is efficient for retrofitting comprehensive objects in heavy pipeline industrial facilities. This work contributes a generic framework for interactive retrofitting in a virtual environment and an unmanned aerial vehicle (UAV)-based sensory setup design to acquire PCD. The framework adopts a 4-in-1 alignment using a point cloud registration algorithm for a pre-processed PCD alignment with the partial PCD, and frame-by-frame registration method for video alignment. This work also proposes a virtual interactive retrofitting framework that uses pre-defined 3D computer-aided design models (CAD) with a customized graphical user interface (GUI) and visualization of a 4-in-1 aligned video scene from a UAV camera in a desktop environment. Trials were carried out using the proposed framework in a real environment at a water treatment facility. A qualitative and quantitative study was conducted to evaluate the performance of the proposed generic framework from participants by adopting the appropriate questionnaire and retrofitting task-oriented experiment. Overall, it was found that the proposed framework could be a solution for interactive 3D CAD model retrofitting on a combination of UAV sensory setup-acquired PCD and real-time video from the camera in heavy industrial facilities.

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“…Yet another practical problem arises when one needs to correctly estimate the pose of the mobile robot. Some works propose strategies that increase localization precision based on vision sensors (Alatise and Hancke, 2017), Global Positioning System (GPS) (Skobeleva et al, 2016), or Light Detection and Ranging (LiDAR) systems (Lima et al, 2016). Most works use the effective sensor fusion techniques and Inertial Measuring Units (IMUs) to combine sensory data from different sensors so that the limitation of individual sensors are compensated.…”

Section: Introductionmentioning

confidence: 99%

LPV Controller Design for Terrestrial Mobile Robot With Tilt Compensation

Filho

Forte

Torrico

et al. 2019

Anais Do 14º Simpósio Brasileiro De Automação Inteligente

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This work presents an LPV (Linear Parameter Varying) controller design for the trajectory tracking problem of nonholonomic wheeled mobile robots (NWMR). The scheduling varying parameters are defined as the feedforward velocities which the robot has to track according to a desired trajectory. The proposed model also includes the robot's motion over a tilted environment. A tilt-compensation scheme is used to maintain the ground speed of the robot if the robot is subjected to an inclination. The compensation is computed on the feedforward velocities. For practical purposes, the inclination angle is measured by an Inertial Measuring Unit. Thus, a sensor fusion model is proposed to fuse data from an accelerometer and a gyroscope. Simulation results are presented in order to evaluate the performance of the controller, sensor fusion and tilt-compensation models.

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Trajectory tracking control of a mobile robot using lidar sensor for position and orientation estimation

Cited by 11 publications

References 10 publications

A C2 continuous trajectory planning method for 6-DOF rotational robot manipulators

A C2 continuous trajectory planning method for 6-DOF rotational robot manipulators

On-Site 4-in-1 Alignment: Visualization and Interactive CAD Model Retrofitting Using UAV, LiDAR’s Point Cloud Data, and Video

LPV Controller Design for Terrestrial Mobile Robot With Tilt Compensation

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