Fault-tolerant control method of robotic arm based on machine vision

Li, Xinmao; Liu, Manlu; Wang, Wei; Li, Yingxing; Li, Minghao

doi:10.1109/ccdc.2018.8407181

Cited by 7 publications

(6 citation statements)

References 5 publications

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“…While the failure in encoder depends on the difference between the measured value and the actual value. The visual joint angle detection method of [27] shows high accurate results with errors values not exceeding ±0.008.…”

Section: 22position and Velocitymentioning

confidence: 94%

“…It is designed depending on finding the difference between normal and faulty signals in its dynamic system. In [27], a fault tolerant and control method is used to detect the angle in joint for a robot arm with backup solution. When an encoder fault happens, a visual joint angle detection method and encoder values are both used to detect the value of angle in robot arm joint.…”

Section: 22position and Velocitymentioning

confidence: 99%

“…When an encoder fault happens, a visual joint angle detection method and encoder values are both used to detect the value of angle in robot arm joint. If any fault happens in encoder value, the visual joint detection method has to be used in real time, where the joint angle is detected using the canny edge detection and the probabilistic Hough transform [27]. The canny edge detection is selected as the best type of edges detection at the expense of consuming more time than other types but it still give a good result when it is used in real time systems [28], [29].…”

Section: 22position and Velocitymentioning

confidence: 99%

“…The canny edge detection is selected as the best type of edges detection at the expense of consuming more time than other types but it still give a good result when it is used in real time systems [28], [29]. The visual mechanism used in [27] needs healthy data as a reference to be compared with the current detected data. While the failure in encoder depends on the difference between the measured value and the actual value.…”

Section: 22position and Velocitymentioning

confidence: 99%

See 3 more Smart Citations

Faults Diagnosis in Robot Systems: A Review

Alobaidy¹,

Abdul–Jabbar²,

Al-Khayyt³

2020

(AREJ)

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Any robot system consists of mechanical and electrical components. These components are combined and compacted together with a special controller to do a specific work. Mostly and with time obsolescence, faults and errors are happen in robot systems lead to work problems. Many years ago, researchers are working in this field. In this paper, a review study focuses on this field is introduced to make classifications between different types of faults and diagnosis methods those used in the field of robotics. Many types of faults are studied, according to some previous and recent works. The most detected faults can be classified into two parts: hardware and software faults. The hardware faults part is further classified into two main types; the first one is represented in sensors and actuators, while the other is included taking into consideration both position and velocity in joints. These joints which usually connect the links of the arm with each other and ensure contentions to motors, controllers, and many sensors, are really represent the most important side have to be studied. The software faults part includes those errors occurred during programming such as any error happen in signal translation, signal classification or signal identification is considered as a software fault. In this paper most of the fault diagnosis and detection methods of faults types in the field of robotics are studied. According to these studied papers, the hardware fault part is the most important part which must be identified and corrected in real time using smart methods.

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Section: 22position and Velocitymentioning

confidence: 94%

Section: 22position and Velocitymentioning

confidence: 99%

Section: 22position and Velocitymentioning

confidence: 99%

Section: 22position and Velocitymentioning

confidence: 99%

See 2 more Smart Citations

Faults Diagnosis in Robot Systems: A Review

Alobaidy¹,

Abdul–Jabbar²,

Al-Khayyt³

2020

(AREJ)

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“…Zhou et al [13] tries to use an improved genetic algorithm to obtain a control strategy to handle actuator failure. Li et al [14] propose a machine vision method to enhance the reliability when robot arm is subject to sensor failure. Piltan et al [15] combine T-S fuzzy algorithm, sliding-mode algorithm and PI observer to improve the robot arm's faulttolerance capacity.…”

Section: Introductionmentioning

confidence: 99%

QR Code-Based Self-Calibration for a Fault-Tolerant Industrial Robot Arm

2019

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Malfunctions on industrial robots can cost factories 22 000 dollars per minute. Although the benefits of a fault-tolerant robot arm are clear, redundant sensors would steeply add to the costs of such robots while machine learning-based methods would spend too much time learning the robot's model. We propose a simple but highly effective method to infer which joint underwent failure and at which angle this joint is constrained and to, then, modify the inverse kinematics (IK) algorithm to adaptively achieve the goal. Our method involves combining the robot arm with a QR code and an inexpensive camera, building a virtual link between these three to give the relative position of the end-effector. Once one joint/encoder/motor suffers damage, we use this virtual link to calibrate this joint by coordinate transformation, to calculate the constrained angle, and to recalculate the trajectory through IK iterations with the Newton-Raphson method. We prove the efficacy of our method with pick-and-place experiments, commonly seen in industrial settings, emulating malfunctions on different joints and at different angles, and our method can successfully finish the task in most cases. We further demonstrate that our method is capable, for almost all of the six-degree-offreedom manipulators, to adapt to joint failures after suffering an actuator failure. With the steep increase of robots within factories, this paper presents an elegant approach to keep robots functional until maintenance is scheduled, reducing downtime.

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