Chengliang Zhang, Jingyi Su, Wenbin Zhang, Jun Zhou
{"title":"Design of Crawler Mobile Car with Infrared Remote Control","authors":"Chengliang Zhang, Jingyi Su, Wenbin Zhang, Jun Zhou","doi":"10.1109/ICCAR49639.2020.9108034","DOIUrl":"https://doi.org/10.1109/ICCAR49639.2020.9108034","url":null,"abstract":"With the rapid development of economy and science and technology, portable mobile platform is an important research content of artificial intelligence. Remote controlled tracked vehicle can not only replace people to explore some location areas, but also have an important impact on the transportation industry. The main body of the remote control crawler car designed in this paper is an integrated frame model. Two DC motors are used to drive the crawler forward. The control mode is infrared remote control. The DC motor is controlled by PWM programmed by single-chip microcomputer. The vehicle can achieve forward, turn and backward operations, and can be well adapted to the complex environment of the road, when using automatic mode, the vehicle can well avoid obstacles.","PeriodicalId":412255,"journal":{"name":"2020 6th International Conference on Control, Automation and Robotics (ICCAR)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133059520","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}
Petra Gospodnetić, Dennis Mosbach, M. Rauhut, H. Hagen
{"title":"Flexible Surface Inspection Planning Pipeline","authors":"Petra Gospodnetić, Dennis Mosbach, M. Rauhut, H. Hagen","doi":"10.1109/ICCAR49639.2020.9107983","DOIUrl":"https://doi.org/10.1109/ICCAR49639.2020.9107983","url":null,"abstract":"Efficiency of a visual inspection system is greatly influenced by the hardware configuration in terms of both arrangement and sensing parameters. Currently, the configuration is still determined manually. The available automated solutions are not yet ready to be integrated into everyday industrial use due to restrictions in applicability. Therefore, this paper offers a holistic approach to development and integration of an inspection planning pipeline which is both modular and application flexible. First, a clear distinction between the automated and semiautomated planning is proposed. Further, a set of requirements is established, ensuring system flexibility. The requirements are independent of the sensing technology and application. Finally, following the requirements, we implemented a semi-automated planning pipeline intended for visual inspection of rigid objects. For the first time, the pipeline introduces a flexibility in terms of object geometry, as well as interactive adaptation of planning results.","PeriodicalId":412255,"journal":{"name":"2020 6th International Conference on Control, Automation and Robotics (ICCAR)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122205320","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}
{"title":"Implementation of an Autonomous Self-Balancing Robot Using Cascaded PID Strategy","authors":"E. Philip, Sharath Golluri","doi":"10.1109/ICCAR49639.2020.9108049","DOIUrl":"https://doi.org/10.1109/ICCAR49639.2020.9108049","url":null,"abstract":"The hardware implementation of an autonomous self-balancing robot, using the open-source Ardupilot platform is presented here. The cascaded PID strategy is combined with a trajectory tracking controller to achieve autonomous driving. Motion and trajectory control performance is analyzed through simulation and hardware based experiments.","PeriodicalId":412255,"journal":{"name":"2020 6th International Conference on Control, Automation and Robotics (ICCAR)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121781575","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}
{"title":"Signal Representation with Optimal Subspace Graph Filtering","authors":"Ying Chen, Jingjing Liu, Lin Zhou, Li Zhao","doi":"10.1109/ICCAR49639.2020.9108105","DOIUrl":"https://doi.org/10.1109/ICCAR49639.2020.9108105","url":null,"abstract":"Signal representation is a prime problem in signal processing. In this paper, we propose a subspace graph filtering method for signal representation. We demonstrate an extended singular value decomposition (SVD) model of signal essentially is a subspace graph filtering, and build a bridge from SVD to graph filtering. A smoothing subspace graph filtering is sequentially learned in the space provided by SVD. In the experiments, we compare the signal restoration performance between the extended SVD and the proposed subspace graph filtering. It shows that clean signal can be better reconstructed from the noisy signal in our smoothing subspace than the SVD space, where the learned smoothed bases of graph filtering are more robust than the bases of SVD to cope with noise.","PeriodicalId":412255,"journal":{"name":"2020 6th International Conference on Control, Automation and Robotics (ICCAR)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122182895","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}
{"title":"Research on Detection Algorithm for Groove Track Wear of Modern Tram","authors":"Jin-Yi Deng, Jian-Jian Xia, Yu Bai, Yutong Liu, Hao Feng, Fang Liu, Yong-Jun Xie","doi":"10.1109/ICCAR49639.2020.9108014","DOIUrl":"https://doi.org/10.1109/ICCAR49639.2020.9108014","url":null,"abstract":"In recent years, modern trams have developed rapidly and groove rails are mainly used for tramway tracks. However, there is less research on the wear detection of groove rails, and even fewer wear detection applications. With the help of the laser triangulation method, this paper developed a set of wear detection of modern tramway groove rails. Among them, a set of data filtering algorithms with self-adaptive function and combined with the geometric characteristics of the groove track are proposed to eliminate data interference points and smooth the data. At the same time, an error correction algorithm is used to correct the detection error angle caused by snake driving, vibration and sensor installation deviation. In addition, this paper also proposes a set of groove rails profile matching algorithms and wear calculation algorithms to achieve accurate measurement of the vertical wear, side wear and total wear of the grooved rail. Experimental verification shows that the wear detection algorithm has strong anti-interference ability and comprehensive data error correction ability.","PeriodicalId":412255,"journal":{"name":"2020 6th International Conference on Control, Automation and Robotics (ICCAR)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130378586","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}
Peizhang Wu, Zongmiao Dai, Jiasheng Liu, Qingyuan Wang
{"title":"Modified Iterative Control for the Base Joints of a Heavy-Load Manipulator","authors":"Peizhang Wu, Zongmiao Dai, Jiasheng Liu, Qingyuan Wang","doi":"10.1109/ICCAR49639.2020.9108067","DOIUrl":"https://doi.org/10.1109/ICCAR49639.2020.9108067","url":null,"abstract":"Aiming at the base joints of heavy-load manipulator for high-precision assembly, this paper proposes a new modified iterative learning controller based on the idea of iterative learning control to solve the problem of low assembly accuracy. According to the kinematic analysis of the base joints for the controlled object, we build the velocity Jacobi relationship between the linear drive slider and the base joints. Further, the traditional and modified iterative learning controller are applied to the angular trajectory tracking for the base joints. The simulation results show that the proposed modified controller can effectively improve the trajectory tracking accuracy than the traditional PD iterative learning controller under the disturbed environment and model mismatched situation.","PeriodicalId":412255,"journal":{"name":"2020 6th International Conference on Control, Automation and Robotics (ICCAR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129414215","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}
Yixin Huang, Shufan Wu, Z. Mu, Xiangyu Long, Sunhao Chu, G. Zhao
{"title":"A Multi-agent Reinforcement Learning Method for Swarm Robots in Space Collaborative Exploration","authors":"Yixin Huang, Shufan Wu, Z. Mu, Xiangyu Long, Sunhao Chu, G. Zhao","doi":"10.1109/ICCAR49639.2020.9107997","DOIUrl":"https://doi.org/10.1109/ICCAR49639.2020.9107997","url":null,"abstract":"Deep-space exploration missions are known as particularly challenging with high risk and cost, as they operate in environments with high uncertainty. The fault of exploration robot can even cause the whole mission to failure. One of the solutions is to use swarm robots to operate missions collaboratively. Compared with a single capable robot, a swarm of less sophisticated robots can cooperate on multiple and complex tasks. Reinforcement learning (RL) has made a variety of progress in multi-agent system autonomous cooperative control domains. In this paper, we construct a collaborative exploration scenario, where a multi-robot system explores an unknown Mars surface. Tasks are assigned to robots by human scientists and each robot takes optimal policies autonomously. The method used to train policies is a multi-agent deep deterministic policy gradient algorithm (MADDPG) and we design an experience sample optimizer to improve this algorithm. The results show that, with the increase of robots and targets number, this method is more efficient than traditional deep RL algorithm in a multi-agent collaborative exploration environment.","PeriodicalId":412255,"journal":{"name":"2020 6th International Conference on Control, Automation and Robotics (ICCAR)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129473748","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}
H. Premachandra, H. Herath, M. P. Suriyage, K. Thathsarana, Y. Amarasinghe, R. Gopura, S. A. Nanayakkara
{"title":"Genetic Algorithm Based Pick and Place Sequence Optimization for a Color and Size Sorting Delta Robot","authors":"H. Premachandra, H. Herath, M. P. Suriyage, K. Thathsarana, Y. Amarasinghe, R. Gopura, S. A. Nanayakkara","doi":"10.1109/ICCAR49639.2020.9108045","DOIUrl":"https://doi.org/10.1109/ICCAR49639.2020.9108045","url":null,"abstract":"Delta Robots are used in industry for light weight material handling and sorting. This paper presents a sequence optimizing methodology for a color and size sorting delta robot. It finds the optimum path in the task space to perform an industry emulated scenario. An OpenCV-Python program was developed to sort objects according to their colors and sizes. The static positional coordinates of the objects in the robot workspace are obtained using the program. Genetic algorithm is used for pick-and-place sequence optimization to ensure that the sorting process is performed in the shortest possible path. The static positional coordinates are used to calculate the fitness. Single point crossover and mutation are applied with elitist selection when the current generation evolves to the next generation. The genetic algorithm ensures that the sequence of pick-and-place converges to the highest fitness in minimum number of generations reducing the computational time.","PeriodicalId":412255,"journal":{"name":"2020 6th International Conference on Control, Automation and Robotics (ICCAR)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128909431","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}
Muhammed Gaafar, M. Magdy, Abdullah T. Elgammal, A. El-Betar, Ahmed M. Saeed
{"title":"Development of a New Compliant Remote Center of Motion (RCM) Mechanism for Vitreoretinal Surgery","authors":"Muhammed Gaafar, M. Magdy, Abdullah T. Elgammal, A. El-Betar, Ahmed M. Saeed","doi":"10.1109/ICCAR49639.2020.9108005","DOIUrl":"https://doi.org/10.1109/ICCAR49639.2020.9108005","url":null,"abstract":"Minimally invasive surgery, especially vitreoretinal surgery, requires high precision micromanipulation for sensitive tissues. Robot-assisted surgery helps to reduce the imperfections of safety, stiffness, and ergonomics. Using Remote Center of Motion mechanism (RCM) in such surgeries ensures rigidity and stability for the manipulation and the safety for the patient. In this paper, a new planer compliant RCM mechanism is proposed. The performance of the proposed compliant mechanism is determined using finite element analysis by ANSYS software. Compliant mechanism with flexure joints achieves the required motion with acceptable rigidity and reduces the demerits of mechanical joints such as friction, backlash, and lubricant. Also, the pseudo-rigid-body method is utilized to model the compliant mechanism as a rigid body. Then, MS-ADAMS software is exploited for the dynamic modelling of the proposed mechanism. The co-simulation between MS-ADAMS and MATLAB is carried out to validate the motion of the mechanism using a PID controller. The results show improvements for the proposed design in terms of parasitic motions, RCM point drift and joint stiffening.","PeriodicalId":412255,"journal":{"name":"2020 6th International Conference on Control, Automation and Robotics (ICCAR)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127032419","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}
Wenbin Zhang, Chengliang Zhang, Jingyi Su, P. Huang, Jun Zhou
{"title":"Design of Automated Medicine-Liquid Proportioning System Based on Spectral Analysis","authors":"Wenbin Zhang, Chengliang Zhang, Jingyi Su, P. Huang, Jun Zhou","doi":"10.1109/ICCAR49639.2020.9108091","DOIUrl":"https://doi.org/10.1109/ICCAR49639.2020.9108091","url":null,"abstract":"The medicine-liquid ratio is an important part of various industries such as medicine and has important applications in the field of medical research. However, the traditional drug-liquid ratios are all artificial ratios, and the efficiency is low. In order to improve the efficiency of practical applications and reduce labor costs, this paper designs a set of automated chemical-liquid ratio system based on spectral analysis. This system takes an ethanol solution as an example. The spectrum analyzer is used to analyze the concentration of ethanol in the chemical solution. The PC reads the concentration information and controls the single-chip computer based on the information. The single-chip computer controls the peristaltic pump to perform the chemical solution ratio to obtain the appropriate concentration of the ethanol solution., Its accuracy is within ± 0.5%.","PeriodicalId":412255,"journal":{"name":"2020 6th International Conference on Control, Automation and Robotics (ICCAR)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128187507","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}