Trajectory Planning and Tracking Control of a Differential-Drive Mobile Robot in a Picture Drawing Application

Shih, Ching‐Long; Lin, Li-Chen

doi:10.3390/robotics6030017

Cited by 30 publications

(17 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Finally, other examples of artistically skilled robots are given by painting mobile platforms, such the ones by L. Moura, who developed Robotic Action Painter in 2006 [27], and by C.-L. Shih, who presented the trajectory planning and control of a mobile robot for drawing applications [28].…”

Section: Related Workmentioning

confidence: 99%

Non-Photorealistic Rendering Techniques for Artistic Robotic Painting

et al. 2019

View full text Add to dashboard Cite

In this paper, we present non-photorealistic rendering techniques that are applied together with a painting robot to realize artworks with original styles. Our robotic painting system is called Busker Robot and it has been considered of interest in recent art fairs and international exhibitions. It consists of a six degree-of-freedom collaborative robot and a series of image processing and path planning algorithms. In particular, here, two different rendering techniques are presented and a description of the experimental set-up is carried out. Finally, the experimental results are discussed by analyzing the elements that can account for the aesthetic appreciation of the artworks.

show abstract

Section: Related Workmentioning

confidence: 99%

Non-Photorealistic Rendering Techniques for Artistic Robotic Painting

et al. 2019

View full text Add to dashboard Cite

show abstract

“…The geometry and kinematic parameters of the differential mobile robot is defined. The position/ orientation vector of the mobile robot and its speed are, respectively [1][2][3][4][5][6][7][8][28][29][30][31][32][33]:…”

Section: The Geometry and Kinematic Of A Mobile Robotmentioning

confidence: 99%

“…Therefore, such problems can be solved through the selection of a suitable curvature and application of a gradual fuzzy gain scheduling of PD control (FGS-PD) control process based on the relationship between the current location of the mobile robot and the target points. Moreover, by controlling the velocities of each of the two wheels attached to the mobile robot through a FGS-PD controller, it is possible to compensate for the slip phenomenon based on the inertial and centrifugal forces acting on the mobile robot as it moves, while minimizing the estimation errors [26][27][28][29][30][31][32][33]. For validating the proposed method, the functions are evaluated by conducting an experiment on the estimation of the sound sources moving in real time in two different situations (straight trajectory and S-curved trajectory) [1][2][3][4][5][6][7][8][28][29][30][31][32][33].…”

Section: Introductionmentioning

confidence: 99%

Tracking Control of Moving Sound Source Using Fuzzy-Gain Scheduling of PD Control

Han

2019

Electronics

View full text Add to dashboard Cite

This paper proposes fuzzy gain scheduling of proportional differential control (FGS-PD) system for tracking mobile robot to moving sound sources. Given that the target positions of the real-time moving sound sources are dynamic, the mobile robots should be able to estimate the target points continuously. In such a case, the robots tend to slip owing to abnormal velocities and abrupt changes in the tracking path. The selection of an appropriate curvature along which the robot follows a sound source makes it possible to ensure that the robot reaches the target sound source precisely. For enabling the robot to recognize the sound sources in real time, three microphones are arranged in a straight formation. In addition, by applying the cross correlation algorithm to the time delay of arrival base, the received signals can be analyzed for estimating the relative positions and velocities of the mobile robot and the sound source. Even if the mobile robot is navigating along a curved path for tracking the sound source, there could be errors due to the inertial and centrifugal forces resulting from the motion of the mobile robot. Velocities of both robot wheels are controlled using FGS-PD control to compensate for slippage and to minimize tracking errors. For experimentally verifying the efficacy of the proposed the control system with sound source estimation, two mobile robots were fabricated. It was demonstrated that the proposed control method effectively reduces the tracking error of a mobile robot following a sound source.

show abstract

“…Real receptors P n , n = 1, …, 8 are IR sensors, real effectors E R,L are the angular velocities of wheels (index R denotes the right wheel, L denotes left one), the control subsystem is described by a nonlinear transition function, derived from state equation (8) after necessary transformations. (10) The dependence between real and virtual receptors in the k-th time moment is following:…”

Section: ʯɩ ďǒƭ ɡʁɂɡɂʊƭƞ řƿƭȭǜ ȧɂƞƭǚmentioning

confidence: 99%

“…Braitenberg algorithm based trajectory planning was considered in [5]. Specific case of path planning in picture drawing application was described in [10]. Following predefined trajectory autonomous robot in indoor transportation was presented in [11].…”

Section: Introductionmentioning

confidence: 99%