Pub Date : 2021-07-15DOI: 10.1109/RCAR52367.2021.9517355
Yongming Yue, Yu Zhang, Wei Gao, Shiwu Zhang
Frequent workload variation is inevitable when legged robots are deployed for human service tasks like package delivery. The varying workloads can be detrimental to the robustness of robots' locomotion and may even cause task failures if no adjustment of the leg controller is applied. To maintain consistent locomotion performance, this paper explores fast gait generation given system workloads using Spring-Loaded Inverted Pendulum based models and advanced Nonlinear Programming tools. Through solving the properly posed optimization problem, the optimal control trajectory can be generated within seconds to help a vertical hopper maintain the desired apex heights, with an error within ±4% under the tested workloads from 48% up to 190% of the robot's weight. The differences among the optimal control trajectories under different workloads for achieving the same or different apex heights necessitates controller adjustment to ensure workload-adaptive locomotion. Additionally, the leg's proprioceptive-only sensing of the ground reaction force during the stance phase reveals a promising way to quantify workload variation, which can then facilitate to close the control loop of workload-adaptive locomotion in the near future.
{"title":"Workload-adaptive Vertical Hopping of A Single-legged Robot using Model-based Optimization","authors":"Yongming Yue, Yu Zhang, Wei Gao, Shiwu Zhang","doi":"10.1109/RCAR52367.2021.9517355","DOIUrl":"https://doi.org/10.1109/RCAR52367.2021.9517355","url":null,"abstract":"Frequent workload variation is inevitable when legged robots are deployed for human service tasks like package delivery. The varying workloads can be detrimental to the robustness of robots' locomotion and may even cause task failures if no adjustment of the leg controller is applied. To maintain consistent locomotion performance, this paper explores fast gait generation given system workloads using Spring-Loaded Inverted Pendulum based models and advanced Nonlinear Programming tools. Through solving the properly posed optimization problem, the optimal control trajectory can be generated within seconds to help a vertical hopper maintain the desired apex heights, with an error within ±4% under the tested workloads from 48% up to 190% of the robot's weight. The differences among the optimal control trajectories under different workloads for achieving the same or different apex heights necessitates controller adjustment to ensure workload-adaptive locomotion. Additionally, the leg's proprioceptive-only sensing of the ground reaction force during the stance phase reveals a promising way to quantify workload variation, which can then facilitate to close the control loop of workload-adaptive locomotion in the near future.","PeriodicalId":232892,"journal":{"name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115313267","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 : 2021-07-15DOI: 10.1109/RCAR52367.2021.9517531
Peijun Zheng, Ruili Dong, Yonghong Tan, Huiyu Wang
Electromagnetic MEMS (Micro-Electro-Mechanical System) micro-mirrors is an optical device that integrates the micro-mirrors lens with a micro-electromechanical system driver using optical micro-electromechanical technology. It will be widely used in the field of laser projection and laser radar. However, the serious less damping characteristics and other nonlinearities exist in the MEMS micro-mirrors systems, which leads to oscillation of the MEMS micro-mirrors system. Hence, a predictive control algorithm for the MEMS micro-mirrors system is proposed. The simulation and experimental results show that the performance of proposed algorithm is meaningful.
{"title":"A Predictive Control for Electromagnetic Scanning Micro-Mirrors","authors":"Peijun Zheng, Ruili Dong, Yonghong Tan, Huiyu Wang","doi":"10.1109/RCAR52367.2021.9517531","DOIUrl":"https://doi.org/10.1109/RCAR52367.2021.9517531","url":null,"abstract":"Electromagnetic MEMS (Micro-Electro-Mechanical System) micro-mirrors is an optical device that integrates the micro-mirrors lens with a micro-electromechanical system driver using optical micro-electromechanical technology. It will be widely used in the field of laser projection and laser radar. However, the serious less damping characteristics and other nonlinearities exist in the MEMS micro-mirrors systems, which leads to oscillation of the MEMS micro-mirrors system. Hence, a predictive control algorithm for the MEMS micro-mirrors system is proposed. The simulation and experimental results show that the performance of proposed algorithm is meaningful.","PeriodicalId":232892,"journal":{"name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115383427","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 : 2021-07-15DOI: 10.1109/RCAR52367.2021.9517600
Dong Wang, Dong Yang, Qinghui Pan, Chaochao Qiu, Y. Dong, Jie Lian
In this paper, we mainly study the pose estimation based on feature matching and manipulator grasping control. Obtaining the pose information of the object is an important part of autonomous grasp of the manipulator. In order to obtain the precise pose information of the object, an improved algorithm is proposed based on the GMS (Grid-Based Motion Statistics) algorithm. Firstly, we use the RANSAC algorithm to remove the point pairs whose the distance error is more than 1.5 pixels after transformation. Secondly, the Euclidean distance of the coefficients is calculated between original image and object image. Some point pairs with a larger distance are removed because of the affine invariant principle. The correct correspondences are transformed from 2D pixel coordinate frame to 3D camera coordinate frame with depth image. The least square method combined with SVD algorithm is used to solve the rotation and translation matrices of the object relative to the camera coordinate frame. These matrices are used to estimate the pose of the object. The high accuracy of feature matching in the improved GMS algorithm is verified. The estimated error of the position $(x, y, z)^{T}$ is within ±2.4mm, and the orientation $(text{Roll}, text{Pitch}, text{Yaw})^{T}$ is within ±1°. Finally, the performance of the algorithm is verified through the grasping experiments with the manipulator.
本文主要研究了基于特征匹配的姿态估计和机械手抓取控制。物体姿态信息的获取是机械臂自主抓取的重要组成部分。为了准确获取目标的姿态信息，在GMS (Grid-Based Motion Statistics)算法的基础上提出了一种改进算法。首先，利用RANSAC算法去除变换后距离误差大于1.5像素的点对;其次，计算原图像与目标图像之间系数的欧氏距离;由于仿射不变性原理，一些距离较大的点对被去除。将正确的对应关系从二维像素坐标帧转换为具有深度图像的三维相机坐标帧。采用最小二乘法结合奇异值分解算法求解目标相对于摄像机坐标系的旋转和平移矩阵。这些矩阵被用来估计物体的姿态。验证了改进的GMS算法具有较高的特征匹配精度。位置$(x, y, z)^{T}$的估计误差在±2.4mm以内，方向$(text{Roll}， text{Pitch}， text{Yaw})^{T}$的估计误差在±1°以内。最后，通过机械手抓取实验验证了算法的性能。
{"title":"Estimating Pose of Object and Manipulator Grasping Control","authors":"Dong Wang, Dong Yang, Qinghui Pan, Chaochao Qiu, Y. Dong, Jie Lian","doi":"10.1109/RCAR52367.2021.9517600","DOIUrl":"https://doi.org/10.1109/RCAR52367.2021.9517600","url":null,"abstract":"In this paper, we mainly study the pose estimation based on feature matching and manipulator grasping control. Obtaining the pose information of the object is an important part of autonomous grasp of the manipulator. In order to obtain the precise pose information of the object, an improved algorithm is proposed based on the GMS (Grid-Based Motion Statistics) algorithm. Firstly, we use the RANSAC algorithm to remove the point pairs whose the distance error is more than 1.5 pixels after transformation. Secondly, the Euclidean distance of the coefficients is calculated between original image and object image. Some point pairs with a larger distance are removed because of the affine invariant principle. The correct correspondences are transformed from 2D pixel coordinate frame to 3D camera coordinate frame with depth image. The least square method combined with SVD algorithm is used to solve the rotation and translation matrices of the object relative to the camera coordinate frame. These matrices are used to estimate the pose of the object. The high accuracy of feature matching in the improved GMS algorithm is verified. The estimated error of the position $(x, y, z)^{T}$ is within ±2.4mm, and the orientation $(text{Roll}, text{Pitch}, text{Yaw})^{T}$ is within ±1°. Finally, the performance of the algorithm is verified through the grasping experiments with the manipulator.","PeriodicalId":232892,"journal":{"name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124395683","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 : 2021-07-15DOI: 10.1109/RCAR52367.2021.9517612
Pengbo Li, Wenhao Wei, Ruoyu Bao, Bailin He, Zhilong Su, Can Wang, Xinyu Wu
A modular rehabilitation exoskeleton robot for hemiplegic patients (SIAT-H) is created in this paper. The design of the exoskeleton is based on the gait analysis of hemiplegic patients and the movement data of healthy people. Through the motion capture experiments at different speeds, the walking style of patients with hemiplegia is understood. A modular exoskeleton robot, including an independent hip joint, knee joint and ankle joint, is designed. The mechanical structure which is optimized based on the physiological characteristics of human body would not cause additional damage to the joints during walking. In order to ensure the reliability of use, the structural strength is also considered. The kinematics relationship is verified by comparison of simulation data and calculated data. In the end, we made an experimental prototype, and the wearing experiment verified the reliability of the mechanism.
{"title":"A Modular Rehabilitation Lower Limb Exoskeleton for Stroke Patients With Hemiplegia","authors":"Pengbo Li, Wenhao Wei, Ruoyu Bao, Bailin He, Zhilong Su, Can Wang, Xinyu Wu","doi":"10.1109/RCAR52367.2021.9517612","DOIUrl":"https://doi.org/10.1109/RCAR52367.2021.9517612","url":null,"abstract":"A modular rehabilitation exoskeleton robot for hemiplegic patients (SIAT-H) is created in this paper. The design of the exoskeleton is based on the gait analysis of hemiplegic patients and the movement data of healthy people. Through the motion capture experiments at different speeds, the walking style of patients with hemiplegia is understood. A modular exoskeleton robot, including an independent hip joint, knee joint and ankle joint, is designed. The mechanical structure which is optimized based on the physiological characteristics of human body would not cause additional damage to the joints during walking. In order to ensure the reliability of use, the structural strength is also considered. The kinematics relationship is verified by comparison of simulation data and calculated data. In the end, we made an experimental prototype, and the wearing experiment verified the reliability of the mechanism.","PeriodicalId":232892,"journal":{"name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"16 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116920293","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 : 2021-07-15DOI: 10.1109/RCAR52367.2021.9517514
Weiqun Wang, Xiruo. Wang, Z. Hou, Zhijie Fang, Yuze Jiao, Yangyu Luo, Jian Gong
A skull reconstruction robot has been developed to effectively overcome shortcomings of the traditional skull surgery and improve its efficiency and quality. In this study, kinematics modeling and trajectory planning for the robot are carried out. Firstly, the kinematic model of the robot is established based on the D-H method. The positioning points, which are used to determine the cutting plane, are given on the surface of the skull by the surgeon. The contour data for cutting can be obtained using a two dimensional laser scanning sensor, by adjusting the scanning light curtain to coincide with the cutting plane. Then, to ensure that the tools fixed at the robot end can always be perpendicular to the skull surface during the cutting or drawing process, the principal component analysis is introduced to design the normal vectors at the selected key points of the point cloud data for the skull surface. Moreover, the quintic polynomial interpolation method is used to construct the curves between the adjacent key points to make up for the defects of the skull surface and ensure the smoothness of the trajectory. Finally, workspace analysis based on Monte Carlo method is implemented, and the proposed kinematics modeling and trajectory planning methods are validated by simulation.
{"title":"Kinematics Modeling and Trajectory Planning for the Skull Reconstruction Robot","authors":"Weiqun Wang, Xiruo. Wang, Z. Hou, Zhijie Fang, Yuze Jiao, Yangyu Luo, Jian Gong","doi":"10.1109/RCAR52367.2021.9517514","DOIUrl":"https://doi.org/10.1109/RCAR52367.2021.9517514","url":null,"abstract":"A skull reconstruction robot has been developed to effectively overcome shortcomings of the traditional skull surgery and improve its efficiency and quality. In this study, kinematics modeling and trajectory planning for the robot are carried out. Firstly, the kinematic model of the robot is established based on the D-H method. The positioning points, which are used to determine the cutting plane, are given on the surface of the skull by the surgeon. The contour data for cutting can be obtained using a two dimensional laser scanning sensor, by adjusting the scanning light curtain to coincide with the cutting plane. Then, to ensure that the tools fixed at the robot end can always be perpendicular to the skull surface during the cutting or drawing process, the principal component analysis is introduced to design the normal vectors at the selected key points of the point cloud data for the skull surface. Moreover, the quintic polynomial interpolation method is used to construct the curves between the adjacent key points to make up for the defects of the skull surface and ensure the smoothness of the trajectory. Finally, workspace analysis based on Monte Carlo method is implemented, and the proposed kinematics modeling and trajectory planning methods are validated by simulation.","PeriodicalId":232892,"journal":{"name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127094676","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 : 2021-07-15DOI: 10.1109/RCAR52367.2021.9517665
Qin Cheng, Ziliang Ren, Jun Cheng, Qieshi Zhang, Hao Yan, Jianming Liu
The skeleton data convey significant information for human action recognition since they can robustly accommodate cluttered background and illumination variation. Early convolutional neural networks (CNN) based method mainly structure the skeleton sequence into pseudo-image and feed it into image classification neural network such as Resnet, which can not capture comprehensive spatial-temporal feature. Recently, graph convolutional networks (GCNs) have obtained superior performance. However, the computational complexity of GCN-based methods is quite high, some works even reach 100 GFLOPs for one action sample. This is contrary to the highly condensed attributes of skeleton data. In this paper, a Multi-scale Spatial-temporal Convolution Neural Network (MSST-Net) is proposed for skeleton-based action recognition. Our MSST-Net abandons complex graph convolutions and takes the implicit complementary advantages across different scales of spatial-temporal representations, which are often ignored in the previous work. On two datasets for action recognition, MSST-Net achieves impressive recognition accuracy with a small amount of calculation.
{"title":"Skeleton-based Action Recognition with Multi-scale Spatial-temporal Convolutional Neural Network","authors":"Qin Cheng, Ziliang Ren, Jun Cheng, Qieshi Zhang, Hao Yan, Jianming Liu","doi":"10.1109/RCAR52367.2021.9517665","DOIUrl":"https://doi.org/10.1109/RCAR52367.2021.9517665","url":null,"abstract":"The skeleton data convey significant information for human action recognition since they can robustly accommodate cluttered background and illumination variation. Early convolutional neural networks (CNN) based method mainly structure the skeleton sequence into pseudo-image and feed it into image classification neural network such as Resnet, which can not capture comprehensive spatial-temporal feature. Recently, graph convolutional networks (GCNs) have obtained superior performance. However, the computational complexity of GCN-based methods is quite high, some works even reach 100 GFLOPs for one action sample. This is contrary to the highly condensed attributes of skeleton data. In this paper, a Multi-scale Spatial-temporal Convolution Neural Network (MSST-Net) is proposed for skeleton-based action recognition. Our MSST-Net abandons complex graph convolutions and takes the implicit complementary advantages across different scales of spatial-temporal representations, which are often ignored in the previous work. On two datasets for action recognition, MSST-Net achieves impressive recognition accuracy with a small amount of calculation.","PeriodicalId":232892,"journal":{"name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126061958","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 : 2021-07-15DOI: 10.1109/RCAR52367.2021.9517489
Junguang Guo, Feifei Gu, Yuping Ye, Zhan Song
As the credibility and accuracy of binocular endoscope reconstruction are significantly affected by narrow baseline and large distortion of taken pictures, we develop a binocular endoscopic speckle system to address these limitations. The system consists of a projector and a binocular endoscope. First, the binocular endoscope captures the object surface, which illuminated by a projector with pseudo-random speckles. Then, we proposed a high-precision calibration method based on three-dimensional to improve the calibration precision of the system. Finally, in order to enhance the exactness and reliability of the stereo matching, Semi-Global Matching (SGM) algorithm is studied and improved. This paper aims to reduce the deviation and improve the 3D measurement accuracy of the system. In comparison with traditional stereo reconstruction, the reconstruction accuracy of cylinder and plane was improved 31.2% and 34.0% respectively.
{"title":"An Accurate Speckle 3D Reconstruction System Based on Binocular Endoscope","authors":"Junguang Guo, Feifei Gu, Yuping Ye, Zhan Song","doi":"10.1109/RCAR52367.2021.9517489","DOIUrl":"https://doi.org/10.1109/RCAR52367.2021.9517489","url":null,"abstract":"As the credibility and accuracy of binocular endoscope reconstruction are significantly affected by narrow baseline and large distortion of taken pictures, we develop a binocular endoscopic speckle system to address these limitations. The system consists of a projector and a binocular endoscope. First, the binocular endoscope captures the object surface, which illuminated by a projector with pseudo-random speckles. Then, we proposed a high-precision calibration method based on three-dimensional to improve the calibration precision of the system. Finally, in order to enhance the exactness and reliability of the stereo matching, Semi-Global Matching (SGM) algorithm is studied and improved. This paper aims to reduce the deviation and improve the 3D measurement accuracy of the system. In comparison with traditional stereo reconstruction, the reconstruction accuracy of cylinder and plane was improved 31.2% and 34.0% respectively.","PeriodicalId":232892,"journal":{"name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"393 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123262034","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}
Various noises in the image will reduce the quality of the image and seriously affect the processing of subsequent computer tasks. The recovery of single images is a more challenging problem than recovery of spectral images due to the lack of spectral information. In order to solve this problem, in this paper, we propose a method combining non-local self-similar priors and tensor decomposition to fully explore the inherent low-rank structure of a single image. Specifically, we use tucker decomposition to characterize the global self-similar patch of a single image. At the same time, we introduce anisotropic spatial-spectral total variation regularization to describe the segmented smooth structure in the image. In order to deal with the complex noise situation in the real scene. We model the noise in two parts, one part is sparse spot noise, and the other part is ubiquitous noise. Then we use the augmented Lagrange multiplier method to solve it. Experiments have proved that the introduction of non-local self-similar priors is crucial to the denoising problem of a single image. The proposed method is superior to all comparison methods.
{"title":"Total Variation Regularized Low-Rank Tensor Decomposition with nonlocal for single image denoising","authors":"Shengchuan Li, Yanmei Wang, Qiong Luo, Kai Wang, Zhi Han, Yandong Tang","doi":"10.1109/RCAR52367.2021.9517668","DOIUrl":"https://doi.org/10.1109/RCAR52367.2021.9517668","url":null,"abstract":"Various noises in the image will reduce the quality of the image and seriously affect the processing of subsequent computer tasks. The recovery of single images is a more challenging problem than recovery of spectral images due to the lack of spectral information. In order to solve this problem, in this paper, we propose a method combining non-local self-similar priors and tensor decomposition to fully explore the inherent low-rank structure of a single image. Specifically, we use tucker decomposition to characterize the global self-similar patch of a single image. At the same time, we introduce anisotropic spatial-spectral total variation regularization to describe the segmented smooth structure in the image. In order to deal with the complex noise situation in the real scene. We model the noise in two parts, one part is sparse spot noise, and the other part is ubiquitous noise. Then we use the augmented Lagrange multiplier method to solve it. Experiments have proved that the introduction of non-local self-similar priors is crucial to the denoising problem of a single image. The proposed method is superior to all comparison methods.","PeriodicalId":232892,"journal":{"name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125341952","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 : 2021-07-15DOI: 10.1109/RCAR52367.2021.9517421
Xiaoxiao Li, Zhihao Xu, Shuai Li, Kanyang Jiang, Xuefeng Zhou, Li Jiang
This paper focuses on the kinematic control of wheeled mobile manipulator with physical limits and external noise disturbances. Based on the quadratic program, a hybrid multi-objective control (HMOC) scheme incorporating path following and physical constraints' compliance is proposed, where the path following task is formulated as an equality constraint. With the velocity escape method, physical limits are incorporated and totally described as an inequality constraint. An integration-enhanced state feedback strategy considering derivation between the robot's real position and the desired position is designed with an aim at achieving anti-noise capability for HMOC scheme, which is shown to improve the tracking performance of the robot in following the desired trajectory under noise disturbances. Lagrangian-based controller is constructed as an online solver of the resultant HMOC scheme to output and update control variables iteratively. With numerical simulation, efficiency of the HMOC scheme and Lagrangian-based controller are validated.
{"title":"Kinematic control of wheeled mobile manipulators subject to inherent physical constraints and noise disturbances","authors":"Xiaoxiao Li, Zhihao Xu, Shuai Li, Kanyang Jiang, Xuefeng Zhou, Li Jiang","doi":"10.1109/RCAR52367.2021.9517421","DOIUrl":"https://doi.org/10.1109/RCAR52367.2021.9517421","url":null,"abstract":"This paper focuses on the kinematic control of wheeled mobile manipulator with physical limits and external noise disturbances. Based on the quadratic program, a hybrid multi-objective control (HMOC) scheme incorporating path following and physical constraints' compliance is proposed, where the path following task is formulated as an equality constraint. With the velocity escape method, physical limits are incorporated and totally described as an inequality constraint. An integration-enhanced state feedback strategy considering derivation between the robot's real position and the desired position is designed with an aim at achieving anti-noise capability for HMOC scheme, which is shown to improve the tracking performance of the robot in following the desired trajectory under noise disturbances. Lagrangian-based controller is constructed as an online solver of the resultant HMOC scheme to output and update control variables iteratively. With numerical simulation, efficiency of the HMOC scheme and Lagrangian-based controller are validated.","PeriodicalId":232892,"journal":{"name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125397023","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 : 2021-07-15DOI: 10.1109/RCAR52367.2021.9517650
Chun Sun, Jing Tang, Xinyu Zhang
Fault tolerance is very important for multi-robot systems, especially for those operated in remote environments. The ability to tolerate failures, allows robots effectively to continue performing tasks without the need for immediate human intervention. In this paper, we present a new efficient fault tolerance algorithm for multi-robot coverage path planning (mCPP). The entire coverage path is considered as a topological task loop. The ideal mCPP problem is handled by partitioning this task loop and assign each partition to individual robot. When a faulty robot is detected, we use an optimization method to minimize the overall maximum coverage cost while considering both the tasks accomplished before robot failures and the remaining tasks. We perform various experiments for regular grid maps and real field terrains. We compare our algorithm against other coverage path planning algorithms and our algorithm outperforms existing spiral-STC-based methods in terms of the overall maximum coverage cost.
{"title":"FT-MSTC*: An Efficient Fault Tolerance Algorithm for Multi-robot Coverage Path Planning","authors":"Chun Sun, Jing Tang, Xinyu Zhang","doi":"10.1109/RCAR52367.2021.9517650","DOIUrl":"https://doi.org/10.1109/RCAR52367.2021.9517650","url":null,"abstract":"Fault tolerance is very important for multi-robot systems, especially for those operated in remote environments. The ability to tolerate failures, allows robots effectively to continue performing tasks without the need for immediate human intervention. In this paper, we present a new efficient fault tolerance algorithm for multi-robot coverage path planning (mCPP). The entire coverage path is considered as a topological task loop. The ideal mCPP problem is handled by partitioning this task loop and assign each partition to individual robot. When a faulty robot is detected, we use an optimization method to minimize the overall maximum coverage cost while considering both the tasks accomplished before robot failures and the remaining tasks. We perform various experiments for regular grid maps and real field terrains. We compare our algorithm against other coverage path planning algorithms and our algorithm outperforms existing spiral-STC-based methods in terms of the overall maximum coverage cost.","PeriodicalId":232892,"journal":{"name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126757792","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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