Image-based visual servoing through micropart reflection for the microassembly process

Chu, Henry K.; Mills, James K.; Cleghorn, W.L.

doi:10.1088/0960-1317/21/6/065016

Cited by 9 publications

(9 citation statements)

References 29 publications

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“…Visual servoing is a common closed-loop visual feedback control approach for object manipulation in robotic research, for example (Bourquardez et al, 2006;Vahrenkamp et al, 2008Vahrenkamp et al, , 2009Siradjuddin et al, 2010;Chu et al, 2011) and industry, for example (Hodges & Hall, 1996;Nomura & Naito, 2000).…”

Section: Image-based Visual Servoingmentioning

confidence: 99%

“…Whereḟ represents the motion of the image feature in consecutive images andq denotes the six dimension velocities, [ẋ,ẏ,ż,ẇ x ,ẇ y ,ẇ z ]: three translations and three rotations of the feature with respect to the camera frame (Chu et al, 2011). Based on the unit focal length perspective projection model, the relationship between the robot arm and the image feature is shown as Equation (2) (Hutchinson et al, 1996;Kragic & Christensen, 2002).…”

Section: Image-based Visual Servoingmentioning

confidence: 99%

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A sketch drawing humanoid robot using image-based visual servoing

Lau

Anderson

Baltes

2019

The Knowledge Engineering Review

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This paper presents our sketch drawing artist humanoid robot research. One of the limitations of the existing artist humanoid robot is the lack of feedback on the error that occurs during the drawing process. The contribution of this research is the development of a humanoid robot artist with drawing error correction capability. Based on our previous work with open-loop control pen-and-ink humanoid robot artist, we have implemented a closed-loop visual servoing approach to address this problem. Our experimental results show that this approach is sufficient to correct drawing errors that occur due to mechanical limitation of a robot.

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Section: Image-based Visual Servoingmentioning

confidence: 99%

Section: Image-based Visual Servoingmentioning

confidence: 99%

A sketch drawing humanoid robot using image-based visual servoing

Lau

Anderson

Baltes

2019

The Knowledge Engineering Review

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“…To evaluate the 3-D positions of the grippers from the vision camera, several researchers have employed a stereo vision system, where 3-D positions can be evaluated through triangulation [18], [19]. An algorithm has been proposed for evaluating the spatial position of a particular micro object from a single camera [20]. The algorithm employed the image reflected from the surface as the additional feature for the evaluation.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Image-Based Force Sensing System Development to Assist Robot-Arm Surgery

Dung-Pham

Cheng

Liu

2021

2021 IEEE International Symposium on Circuits and Systems (ISCAS)

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It is generally accepted that robotic surgery has increased in popularity which has revolutionized the medical field over the past few decades. Despite many successes and development, there are still a lot of challenges what was remained in the surgeries such as the requirement of haptic feedback system has become a raising issue due to a lot of failure cases during robotic surgery processes, for example: suture breakage because of pulling action in knot-tying, slipped on a needle of grasping action or inadequate of force. In this paper, an image-based force sensing feedback system is presented. The force feedback system can provide unmistakable for the surgeon how much force they are utilizing by showing corresponding colors, which can reduce instances of surgery failure without negatively impacting the surgeon's performance. Visual images-based were employed to watching the distance changing of plasticity sensor during the time it was suffering an opposite reaction force from grasping action of a surgery robot arm. From the experiments, this visual images-based evaluation method can detect a minimum force value of 0.01 Newton. This system provides extraordinary accuracy of force sensing feedback and also hands controlling for a robot arm, due to the accuracy shows up to 99.96% (hands action recognition). The main distribution of this studying is to give robot-arm can use the proposed technique to estimate and utilize force values for surgical operation.

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“…To evaluate 3D positions of the grippers from the vision camera, J. R. R. Mayer et al [14] and El-Haddad et al [15] employed a stereo-vision system, where 3D positions can be evaluated through triangulation. Chu et al [16] proposed an algorithm for evaluating the spatial position of a particular micro-object from a single camera. The algorithm employed the image reflected from the surface as the additional feature for the evaluation.…”

Section: Introductionmentioning

confidence: 99%

Vision-Based Surgical Suture Looping Through Trajectory Planning for Wound Suturing

Chu

Huang

et al. 2019

IEEE Trans. Automat. Sci. Eng.

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Robot-assisted surgery (RAS) has revolutionized the field of surgery over the past few decades. Despite many successes, achieving full automation in these surgeries remains a challenging task. In this paper, a dynamic approach is proposed to automate knot tying with an in-house robot vision system. Through efficient path planning and coordination between two grippers, the workspace required for constructing the suture loop can be reduced while issues such as suture slippage and collisions between instruments can be eliminated. Visual images were employed to monitor the two grippers in real-time and their positions were evaluated using transformation matrices obtained experimentally. A Linear Quadratic (LQ) control scheme was applied to optimize the tracking performance of the two grippers.From the experiments, this visual evaluation method can achieve a position accuracy of 1 mm in the workspace. The proposed algorithm was evaluated and automatic suture looping operation was successfully performed in all six trials. Different parameters in the control scheme were also examined by introducing external impulse disturbances during the knot tying process. This proposed knot-tying approach demonstrates a simple and efficient way to construct a suture knot in a minimal workspace. Note to Practitioners -A surgical operation usually takes several hours to complete, which is a test of surgeon's endurance. To better assist surgeons, several repetitive surgical tasks can be performed automatically with a robotic system. This paper presents a new method for robot-assisted surgical knot tying in a confined environment. Through simultaneous manipulation and trajectory planning of the two surgical grippers, suture loops were constructed while keeping the suture in tension. Images were employed to guide the gripers in completing the knot tying process with high precision. Experiments were conducted to demonstrate the automated suture looping operation with the system and the proposed method. The robustness of the method was also examined by introducing impulse disturbances and occlusions during the experiments. This proposed method does not require complicated hardware setup, allowing easy implementations on various surgical systems.

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Image-based visual servoing through micropart reflection for the microassembly process

Cited by 9 publications

References 29 publications

A sketch drawing humanoid robot using image-based visual servoing

A sketch drawing humanoid robot using image-based visual servoing

An Intelligent Image-Based Force Sensing System Development to Assist Robot-Arm Surgery

Vision-Based Surgical Suture Looping Through Trajectory Planning for Wound Suturing

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