Obstacle avoidance control for a human-operated mobile robot

Uchiyama, Naoki; Hashimoto, Tatsuhiro; Sano, Shigenori; Takagi, Shoji

doi:10.1109/amc.2008.4516112

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…In precision manufacturing, it is recommended to apply contouring control as it relates directly to the shape of the desired workpiece [6]. On the tracking approaches [7][8][9], the axial controllers are used to reduce the tracking error and thereby indirectly reduce the resultant contour error.…”

Section: Introductionmentioning

confidence: 99%

Simple adaptive contouring control for feed drive systems using jerk-based augmented output signal

Nyobuya,

Halinga,

Uchiyama

2024

Int J Adv Manuf Technol

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Reducing energy consumption while maintaining high contouring accuracy for industrial machinery is a highly desirable goal. Simple adaptive control (SAC) is a practical technique that can achieve high tracking accuracy and energy saving by adjusting control parameters in real-time to ensure that the system responds as the reference model. Implementation of the SAC technique requires that the "almost strict property real (ASPR)" property is satisfied. The ASPR property guarantees the stability of the controlled system even when adaptive gains are high. This paper proposes simple adaptive contouring control (SACC) using jerk-based augmented output signal for the ASPR property. SACC is designed by following the tangent-contour control scheme while using the SAC technique to enhance the contouring accuracy. Jerk-based augmented output signal ensures that the ASPR property is met and allows the SACC to track accurately the desired contour at high frequency. The proposed contouring approach achieves lower contour error and energy consumption by about 45%, and 3% respectively, as compared to the most common parallel feedforward compensation approach.

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Section: Introductionmentioning

confidence: 99%

Simple adaptive contouring control for feed drive systems using jerk-based augmented output signal

Nyobuya,

Halinga,

Uchiyama

2024

Int J Adv Manuf Technol

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“…In particular, wheeled mobile robots are highly expected to be utilized and hence have been extensively studied in terms of path planning, trajectory tracking control, localization, and navigation. [1][2][3][4][5][6][7][8][9][10][11] Mobile robots normally operate in environments occupied by obstacles; therefore, they must be equipped with an obstacle avoidance capability. Moreover, some obstacles may move or change over time, requiring the algorithm to be updated on a continuous basis.…”

Section: Introductionmentioning

confidence: 99%

Vision-based smooth obstacle avoidance motion trajectory generation for autonomous mobile robots using Bézier curves

Simba

Uchiyama

Aldibaja

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part C:

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This paper proposes an obstacle avoidance trajectory generation method that provides a smooth trajectory in real time. The trajectory is generated from an environmental top-view image, where a fisheye lens is used to capture a wide area at low height. Corners of the obstacles are detected and corrected using the log-polar transform and are used to generate a simple configuration space that reduces the computation time. An optimal path is computed by using the A[Formula: see text] algorithm and replaced by a smooth trajectory generated based on piecewise quintic Bézier curves. Based on the established goal and visual information, a method for generating the first and second derivatives at the start and end points of each Bézier segment is proposed to generate a continuous curvature trajectory. The method is simple and easy to implement and has an average computation time of 1.17s on a PC (CPU: 1.4 GHz) for a workspace containing five to six obstacles. Experimental results verify that the proposed method is effective for real-time motion planning of autonomous mobile robots.

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Real-time smooth trajectory generation for nonholonomic mobile robots using Bézier curves

Simba

Uchiyama

Sano

2016

Robotics and Computer-Integrated Manufacturing

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Obstacle avoidance control for a human-operated mobile robot

Cited by 6 publications

References 10 publications

Simple adaptive contouring control for feed drive systems using jerk-based augmented output signal

Simple adaptive contouring control for feed drive systems using jerk-based augmented output signal

Vision-based smooth obstacle avoidance motion trajectory generation for autonomous mobile robots using Bézier curves

Real-time smooth trajectory generation for nonholonomic mobile robots using Bézier curves

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