Pub Date : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053887
Shibo Na, Ruizhuo Song
In this paper, we proposed an adaptive dynamic programming (ADP) algorithm for discrete time stochastic linear quadratic game without system dynamics. Firstly, we described the problem and converted it into a deterministic form. Then, we solved the Bellman equation to obtain the control gain matrix and disturbance gain matrix when the system dynamics were known. After that, we implemented the ADP algorithm with unknown system through neural networks. Model network, action network, disturbance network and critic network were used to approximate the system model, control gain matrix, disturbance gain matrix and value function respectively. Finally, a simulation example was given to verify the effectiveness of the algorithm.
{"title":"Stochastic Linear Quadratic Game for Discrete-time Systems Based-on Adaptive Dynamic Programming","authors":"Shibo Na, Ruizhuo Song","doi":"10.1109/ICCR55715.2022.10053887","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053887","url":null,"abstract":"In this paper, we proposed an adaptive dynamic programming (ADP) algorithm for discrete time stochastic linear quadratic game without system dynamics. Firstly, we described the problem and converted it into a deterministic form. Then, we solved the Bellman equation to obtain the control gain matrix and disturbance gain matrix when the system dynamics were known. After that, we implemented the ADP algorithm with unknown system through neural networks. Model network, action network, disturbance network and critic network were used to approximate the system model, control gain matrix, disturbance gain matrix and value function respectively. Finally, a simulation example was given to verify the effectiveness of the algorithm.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128009250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053889
He Zhong, Jiangtao Liu, Mingwei Tang, Jianlei Zhang, Kai Liu, Song Xiao, Yujun Guo
During the operational process of the metro lines, the traction current discharged from the working grounding wheels flows back to the terrestrial traction substations through the steel rail, as the DC stray current may be generated due to the poor insulating condition between the rail and the ground. The characteristics of the DC stray current invading the transformer settled at the terrestrial substation is affected by a series elements including the train's operational condition, the ‘rail -ground’ transition resistance, the soil structure and power grid topology. Exploring the influence factors of the stray current lays the foundations for further preventing the negative impact brought from stray current. In order to analyze the influence of the power grid topology on the stray current invading transformers, a coupling model involving the up and down metro lines with the power grid is built, based on the finite element method (FEM). Based on this FEM model, the variation of stray current invading the transformer is analyzed along with the relative position between the power grid single circuit and the metro line varying, meanwhile the variation of the power grid's topology is also considered. It is found that with the complexity of the power grid topology, the total amount of stray current invading the power grid increases, whereas the stray current flowing through the majority of the transmission lines decreases. In addition, no matter the two transformers constituting the power grid circuit are on the same side or on the opposite side of the metro line, the stray current invading the grid tends to increase with the reduction of the angle between the metro line and the power grid circuit.
{"title":"The Influence Analysis of the Power Grid Topology on the Stray Current Invading Transformers","authors":"He Zhong, Jiangtao Liu, Mingwei Tang, Jianlei Zhang, Kai Liu, Song Xiao, Yujun Guo","doi":"10.1109/ICCR55715.2022.10053889","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053889","url":null,"abstract":"During the operational process of the metro lines, the traction current discharged from the working grounding wheels flows back to the terrestrial traction substations through the steel rail, as the DC stray current may be generated due to the poor insulating condition between the rail and the ground. The characteristics of the DC stray current invading the transformer settled at the terrestrial substation is affected by a series elements including the train's operational condition, the ‘rail -ground’ transition resistance, the soil structure and power grid topology. Exploring the influence factors of the stray current lays the foundations for further preventing the negative impact brought from stray current. In order to analyze the influence of the power grid topology on the stray current invading transformers, a coupling model involving the up and down metro lines with the power grid is built, based on the finite element method (FEM). Based on this FEM model, the variation of stray current invading the transformer is analyzed along with the relative position between the power grid single circuit and the metro line varying, meanwhile the variation of the power grid's topology is also considered. It is found that with the complexity of the power grid topology, the total amount of stray current invading the power grid increases, whereas the stray current flowing through the majority of the transmission lines decreases. In addition, no matter the two transformers constituting the power grid circuit are on the same side or on the opposite side of the metro line, the stray current invading the grid tends to increase with the reduction of the angle between the metro line and the power grid circuit.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126735410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053914
Puyang Liu, Song Xiao, Jie Liu, Chuanming Sun, Zuoqin Zhang, Junzhang Duan, Ye Cao, Jie Yu
The insulation section is an important part of the track circuit and plays a great role in judging the position of the train and the electrical isolation of the track circuit signal. As high-speed railway continue to increase speed, maintaining the high-speed operation of the train will inevitably require a larger traction current. When the train passes through the insulation section, the large rail current will frequently appear to be briefly disconnected, and the arcing phenomenon will often occur between the wheel and rail. Due to the high traction rail current and overvoltage caused by the higher grade arc will burn the insulation section, resulting in damage to the insulation section, which will greatly affect the operation safety of the train when it is serious. Based on the “train-rail” circuit model constructed, this paper discusses that when the running speed of the train is 100km/h, the switch and resistance are connected in series between adjacent rails. Then the rail current when the train passes through the insulation section is reduced by controlling the resistance, so as to reduce the level of arcing, reduce the impact of current on the rail, and effectively ensure the safe and stable operation of the train.
{"title":"Rail Current Suppression Strategy for Trains Passing through Insulation Section","authors":"Puyang Liu, Song Xiao, Jie Liu, Chuanming Sun, Zuoqin Zhang, Junzhang Duan, Ye Cao, Jie Yu","doi":"10.1109/ICCR55715.2022.10053914","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053914","url":null,"abstract":"The insulation section is an important part of the track circuit and plays a great role in judging the position of the train and the electrical isolation of the track circuit signal. As high-speed railway continue to increase speed, maintaining the high-speed operation of the train will inevitably require a larger traction current. When the train passes through the insulation section, the large rail current will frequently appear to be briefly disconnected, and the arcing phenomenon will often occur between the wheel and rail. Due to the high traction rail current and overvoltage caused by the higher grade arc will burn the insulation section, resulting in damage to the insulation section, which will greatly affect the operation safety of the train when it is serious. Based on the “train-rail” circuit model constructed, this paper discusses that when the running speed of the train is 100km/h, the switch and resistance are connected in series between adjacent rails. Then the rail current when the train passes through the insulation section is reduced by controlling the resistance, so as to reduce the level of arcing, reduce the impact of current on the rail, and effectively ensure the safe and stable operation of the train.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115547930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053929
Chenxi Guan, Shuying Wang
When the traditional A* algorithm is applied to robot path planning, it has the problems of low efficiency and unable to avoid obstacles dynamically. In order to solve the above problems, a fusion algorithm based on improved A* algorithm and DWA algorithm is proposed. The A* algorithm is improved in three aspects: reducing the search direction of A* algorithm to reduce the search time, adding path information parameters to dynamically adjust the weight of heuristic function, and introducing important node extraction strategy to reduce the number of turns and shorten the path. Finally, the improved A* algorithm is fused with DWA algorithm. The experimental results show that the improved fusion algorithm can realize global optimal path planning and local real-time obstacle avoidance.
{"title":"Robot Dynamic Path Planning Based on Improved A* and DWA Algorithms","authors":"Chenxi Guan, Shuying Wang","doi":"10.1109/ICCR55715.2022.10053929","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053929","url":null,"abstract":"When the traditional A* algorithm is applied to robot path planning, it has the problems of low efficiency and unable to avoid obstacles dynamically. In order to solve the above problems, a fusion algorithm based on improved A* algorithm and DWA algorithm is proposed. The A* algorithm is improved in three aspects: reducing the search direction of A* algorithm to reduce the search time, adding path information parameters to dynamically adjust the weight of heuristic function, and introducing important node extraction strategy to reduce the number of turns and shorten the path. Finally, the improved A* algorithm is fused with DWA algorithm. The experimental results show that the improved fusion algorithm can realize global optimal path planning and local real-time obstacle avoidance.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131467692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053879
Lulu Zhou, Chen Peng, Z. Cao
This paper is concerned with the collaborative design of networked control systems (NCSs) subject to DoS attacks, scheduling protocols, and time-varying delays. First, to save limited network resources and prevent data collisions, the Try-Once-Discard (TOD) protocol is introduced to orchestrate the node access assignment in the sensor-to-controller channel. Then, denial-of-service (DoS) attacks that can cause communication blockages are addressed. Additionally, sufficient conditions are derived to guarantee the exponential mean-square stability of the resulting hybrid system based on which the controller gain and weighted matrix of scheduling protocols are co-designed. Finally, two simulation examples are used to illustrate the validity of the proposed method.
{"title":"Communication and Control Co-design for Networked Control Systems under DoS Attacks and Time-varying Delays","authors":"Lulu Zhou, Chen Peng, Z. Cao","doi":"10.1109/ICCR55715.2022.10053879","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053879","url":null,"abstract":"This paper is concerned with the collaborative design of networked control systems (NCSs) subject to DoS attacks, scheduling protocols, and time-varying delays. First, to save limited network resources and prevent data collisions, the Try-Once-Discard (TOD) protocol is introduced to orchestrate the node access assignment in the sensor-to-controller channel. Then, denial-of-service (DoS) attacks that can cause communication blockages are addressed. Additionally, sufficient conditions are derived to guarantee the exponential mean-square stability of the resulting hybrid system based on which the controller gain and weighted matrix of scheduling protocols are co-designed. Finally, two simulation examples are used to illustrate the validity of the proposed method.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132394862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053878
Yuge Xu, Shuqiao Yang, Xie Zhang, Ziyi Xie
Steel surface defects Detection is crucial to improving the quality of steel production. However, the high-speed production lines, defect diversification, and tiny defects make the detection of steel surface defects difficult. This paper presents a steel surface defects detection model based on an improved Faster R-CNN. Firstly, to improve the generalization of the model, the ResNet50 network is replaced by the RegNet network. Then the transformer spatial attention is utilized to make the network focus more on the targets. Finally, transfer learning, multi-scale training, and cosine annealing learning rate are used to further improve the detection accuracy. Compared with the other nine models, the proposed model has superior performance in the simulation results. The improved model can effectively improve the accuracy of steel surface defects detection.
{"title":"Steel Surface Defects Detection Based on Improved Faster R-CNN","authors":"Yuge Xu, Shuqiao Yang, Xie Zhang, Ziyi Xie","doi":"10.1109/ICCR55715.2022.10053878","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053878","url":null,"abstract":"Steel surface defects Detection is crucial to improving the quality of steel production. However, the high-speed production lines, defect diversification, and tiny defects make the detection of steel surface defects difficult. This paper presents a steel surface defects detection model based on an improved Faster R-CNN. Firstly, to improve the generalization of the model, the ResNet50 network is replaced by the RegNet network. Then the transformer spatial attention is utilized to make the network focus more on the targets. Finally, transfer learning, multi-scale training, and cosine annealing learning rate are used to further improve the detection accuracy. Compared with the other nine models, the proposed model has superior performance in the simulation results. The improved model can effectively improve the accuracy of steel surface defects detection.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129593698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053931
Yongxin Liu, Qiang He, Junhui Wang, Zhiliang Wang, Tianheng Chen, Shichen Jin, Chi Zhang, Zhiqiang Wang
In order to reduce the cost of human resources and material resources and improve the power line inspection efficiency, unmanned ground vehicle (UGV), which utilizes the modern artificial intelligence such as deep learning and reinforcement learning, is commonly introduced to replace of human to inspect power lines in the grid system. This paper provides a deep Q network (DQN) and convolutional neural network (CNN) based end-to-end control model to drive UGV to inspect automatically, and meanwhile to avoid obstacles. Specifically, we utilize the preprocessed grayscale image as the input of the CNN, and output the final Q value. This model simulates human learning behavior by interaction between UGV and the environment. Through repeated self-learning and reward value increasing in a simulation environment, the UGV successfully reaches the target position in a shortest time and meanwhile avoiding a variety of obstacles.
{"title":"Convolutional Neural Network Based Unmanned Ground Vehicle Control via Deep Reinforcement Learning","authors":"Yongxin Liu, Qiang He, Junhui Wang, Zhiliang Wang, Tianheng Chen, Shichen Jin, Chi Zhang, Zhiqiang Wang","doi":"10.1109/ICCR55715.2022.10053931","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053931","url":null,"abstract":"In order to reduce the cost of human resources and material resources and improve the power line inspection efficiency, unmanned ground vehicle (UGV), which utilizes the modern artificial intelligence such as deep learning and reinforcement learning, is commonly introduced to replace of human to inspect power lines in the grid system. This paper provides a deep Q network (DQN) and convolutional neural network (CNN) based end-to-end control model to drive UGV to inspect automatically, and meanwhile to avoid obstacles. Specifically, we utilize the preprocessed grayscale image as the input of the CNN, and output the final Q value. This model simulates human learning behavior by interaction between UGV and the environment. Through repeated self-learning and reward value increasing in a simulation environment, the UGV successfully reaches the target position in a shortest time and meanwhile avoiding a variety of obstacles.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125168325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053885
Shujun Huang, Zhihua Zhang, Ruofeng Xie
The use of wireless sensor networks can achieve effective protection of the monitored area. The node deployment and energy saving optimization of wireless sensor network is important due to the constraints of limited battery capacity and short life span of nodes, and a node deployment and energy saving optimization method is proposed based on reinforcement learning. The Q-learning algorithm is used to screen the nodes that can detect the range of small animals, deploy the nodes autonomously and achieve effective energy saving optimization. Simulation results show that the method can reduce energy consumption by 30% to 35% with shorter convergence time.
{"title":"Node Deployment and Energy Saving Optimization Method for Wireless Sensor Networks Based on Q-learning","authors":"Shujun Huang, Zhihua Zhang, Ruofeng Xie","doi":"10.1109/ICCR55715.2022.10053885","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053885","url":null,"abstract":"The use of wireless sensor networks can achieve effective protection of the monitored area. The node deployment and energy saving optimization of wireless sensor network is important due to the constraints of limited battery capacity and short life span of nodes, and a node deployment and energy saving optimization method is proposed based on reinforcement learning. The Q-learning algorithm is used to screen the nodes that can detect the range of small animals, deploy the nodes autonomously and achieve effective energy saving optimization. Simulation results show that the method can reduce energy consumption by 30% to 35% with shorter convergence time.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114343136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053863
X. Liu, Lei Zhang, Yunjian Peng
In this paper, an adaptive optimal control is investigated for a stochastic linear discrete-time system with multiplicative state-dependent noise and control-dependent noise without knowledge of the system dynamics. With the framework of Q-learning, an off-policy state feedback solution for stochastic linear quadratic tracking (SLQT) problem has been proposed. First, an augmented system of the original system and the reference command generator is established to solve SLQT problem. Then, we present an optimal control by solving stochastic algebraic Riccati equation (SARE). Next, we present the on-policy and off-policy algorithms to achieve an adaptive optimal control without knowing the system dynamics. Finally, a simulation test is finally setup to verify the performance of the proposed adaptive optimal control.
{"title":"Off-policy Q-learning-based Tracking Control for Stochastic Linear Discrete-Time Systems","authors":"X. Liu, Lei Zhang, Yunjian Peng","doi":"10.1109/ICCR55715.2022.10053863","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053863","url":null,"abstract":"In this paper, an adaptive optimal control is investigated for a stochastic linear discrete-time system with multiplicative state-dependent noise and control-dependent noise without knowledge of the system dynamics. With the framework of Q-learning, an off-policy state feedback solution for stochastic linear quadratic tracking (SLQT) problem has been proposed. First, an augmented system of the original system and the reference command generator is established to solve SLQT problem. Then, we present an optimal control by solving stochastic algebraic Riccati equation (SARE). Next, we present the on-policy and off-policy algorithms to achieve an adaptive optimal control without knowing the system dynamics. Finally, a simulation test is finally setup to verify the performance of the proposed adaptive optimal control.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114540501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-02DOI: 10.1109/ICCR55715.2022.10053894
Weibing Li, Biao Song, Yongping Pan
In minimally invasive surgery (MIS), a surgical endoscope is an essential instrument that provides visualization for the surgeon. One principal characteristic of surgical instruments is that remote center of motion (RCM) must be respected. To meet such a practical requirement, many physical RCM mechanisms and software-based RCM generation algorithms have been proposed. As compared with physical RCM mechanisms, RCM generation algorithms possess more flexibility due to the fact that the RCM point can be adjusted if required. This paper conducts comparisons of four typical RCM generation algorithms applied to a vision-controlled robotic endoscope under joint constraints. Kinematic models of the robotic endoscope and the four RCM generation algorithms are first briefly introduced. Then, a unified control formulation based on quadratic programming (QP) is constructed to incorporate kinematic, RCM, and physical constraints of the robotic endoscope. Based on the unified control scheme, comparative simulations and experiments are performed. The advantages and disadvantages of the four typical RCM generation algorithms are analyzed and discussed. When performing a same peg transfer task in the simulations, the RCM errors synthesized by RCM generation algorithms designed using a plane equation and an insertion equation are smaller. In the physical experiments, there are few differences in the RCM errors. Nevertheless, it is revealed that the joint velocities corresponding to the RCM generation algorithm based on a plane equation are the smallest, which means that the joint angles change more gently and it can be more friendly to MIS.
{"title":"Comparisons of RCM Generation Algorithms for Vision-Controlled Robotic Endoscope","authors":"Weibing Li, Biao Song, Yongping Pan","doi":"10.1109/ICCR55715.2022.10053894","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053894","url":null,"abstract":"In minimally invasive surgery (MIS), a surgical endoscope is an essential instrument that provides visualization for the surgeon. One principal characteristic of surgical instruments is that remote center of motion (RCM) must be respected. To meet such a practical requirement, many physical RCM mechanisms and software-based RCM generation algorithms have been proposed. As compared with physical RCM mechanisms, RCM generation algorithms possess more flexibility due to the fact that the RCM point can be adjusted if required. This paper conducts comparisons of four typical RCM generation algorithms applied to a vision-controlled robotic endoscope under joint constraints. Kinematic models of the robotic endoscope and the four RCM generation algorithms are first briefly introduced. Then, a unified control formulation based on quadratic programming (QP) is constructed to incorporate kinematic, RCM, and physical constraints of the robotic endoscope. Based on the unified control scheme, comparative simulations and experiments are performed. The advantages and disadvantages of the four typical RCM generation algorithms are analyzed and discussed. When performing a same peg transfer task in the simulations, the RCM errors synthesized by RCM generation algorithms designed using a plane equation and an insertion equation are smaller. In the physical experiments, there are few differences in the RCM errors. Nevertheless, it is revealed that the joint velocities corresponding to the RCM generation algorithm based on a plane equation are the smallest, which means that the joint angles change more gently and it can be more friendly to MIS.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131787790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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