2023 8th International Conference on Control and Robotics Engineering (ICCRE)最新文献

Camera Image Based Moving Platform Rotation Estimation for Quadrotor Landing 基于相机图像的四旋翼飞行器运动平台旋转估计

2023 8th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2023-04-21 DOI: 10.1109/ICCRE57112.2023.10155600

Joonyoung Jang, M. Macias, T. Bewley

引用次数: 0

A Hybrid Bayesian Network Structure Learning Algorithm in Equivalence Class Space 等价类空间中的混合贝叶斯网络结构学习算法

2023 8th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2023-04-21 DOI: 10.1109/ICCRE57112.2023.10155599

Xiaohan Liu, Xiaoguang Gao, Xinxin Ru, Zidong Wang

引用次数: 0

Estimating the Maximum Pushing Force of Robot Manipulators to Physically Assist Caregivers 估计机器人操作器的最大推力，以帮助照顾者

2023 8th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2023-04-21 DOI: 10.1109/ICCRE57112.2023.10155588

C. Kowalski, S. Hellmers, Pascal Hinrichs, Andreas Hein

引用次数: 0

An End-to-End Pose Estimation Network for Multiscale Space Non-cooperative Objects 多尺度空间非合作目标的端到端姿态估计网络

2023 8th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2023-04-21 DOI: 10.1109/ICCRE57112.2023.10155575

Yizhe Cao, Xianghong Cheng

{"title":"An End-to-End Pose Estimation Network for Multiscale Space Non-cooperative Objects","authors":"Yizhe Cao, Xianghong Cheng","doi":"10.1109/ICCRE57112.2023.10155575","DOIUrl":"https://doi.org/10.1109/ICCRE57112.2023.10155575","url":null,"abstract":"The pose estimation method of space non-cooperative objects based on deep learning is of great significance for further improving the on-orbit service level. However, at present, the pose estimation method of space non-cooperative objects based on deep learning still has some problems, such as relying on a priori 3D wireframe model, the network is not lightweight enough, and the precision of pose estimation for multiscale objects is not high. Therefore, this paper proposes an end-to-end pose estimation network for multiscale space non-cooperative objects. First, the lightweight EfficientNet-B0 is selected as the backbone, and feature pyramid network is introduced into EfficientNet-B0 to improve the pose estimation precision of the network for non-cooperative objects at middle and far distance. Then, a pose prediction head network including object loss function and pose loss function is designed. Finally, a lightweight and multiscale pose estimation network for space non-cooperative objects is established. The simulation results in SwissCube dataset show that the proposed pose estimation network has an average precision improvement of 3.6% compared with advanced methods. In addition, compared with other backbones, the “EfficientNet-B0+FPN” improves the average precision by 7.6% and is lighter.","PeriodicalId":285164,"journal":{"name":"2023 8th International Conference on Control and Robotics Engineering (ICCRE)","volume":"15 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131938292","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}

引用次数: 0

A Digital Twin-Based Production-Maintenance Joint Scheduling Framework with Reinforcement Learning 基于数字孪生的强化学习生产-维修联合调度框架

2023 8th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2023-04-21 DOI: 10.1109/ICCRE57112.2023.10155592

Qinglong Hao, Yaqiong Lv

引用次数: 0

An Assessment of Predictive Control Strategies for Lateral Stability Control of 4-Wheels Drive Electrical Vehicle 四轮驱动电动汽车横向稳定性预测控制策略评估

2023 8th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2023-04-21 DOI: 10.1109/ICCRE57112.2023.10155598

A. Hassan, J. R. D. Frejo, J. Maestre

{"title":"An Assessment of Predictive Control Strategies for Lateral Stability Control of 4-Wheels Drive Electrical Vehicle","authors":"A. Hassan, J. R. D. Frejo, J. Maestre","doi":"10.1109/ICCRE57112.2023.10155598","DOIUrl":"https://doi.org/10.1109/ICCRE57112.2023.10155598","url":null,"abstract":"Distributed electric drive vehicles offer convenience and maneuverability, but distributing torque to all four wheels to ensure stability under various driving conditions can be a challenge. This paper presents a novel control strategy for torque vector control using both linear and nonlinear model predictive control (MPC) as an optimal way to generate additional yaw moment, which improves handling stability while also maintaining accuracy in trajectory tracking. This strategy combines handling, lateral stability, and ride comfort. The MPC and nonlinear MPC controllers are designed to follow reference values and improve handling and lateral stability by calculating the total required torque while minimizing tracking errors in sideslip and yaw angle. The torque for each wheel is then determined based on yaw moment and longitudinal force using low-level torque vector synthesis. The optimized control sequence is then sent to the actuator. Simulations in different road conditions for pathfollowing scenarios were conducted in MATLAB/Simulink, and the proposed nonlinear MPC method was found to be superior to the ordinary MPC-based direct yaw method.","PeriodicalId":285164,"journal":{"name":"2023 8th International Conference on Control and Robotics Engineering (ICCRE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131171654","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}

引用次数: 0

A Feature Structure Based Interpretability Evaluation Approach for Deep Learning 基于特征结构的深度学习可解释性评价方法

2023 8th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2023-04-21 DOI: 10.1109/ICCRE57112.2023.10155583

X. Li, Xiaoguang Gao, Chenfeng Wang, Qianglong Wang

引用次数: 0

Constrained Motion Planning for a Robotic Endoscope Holder Based on Hierarchical Quadratic Programming 基于层次二次规划的机器人内窥镜支架约束运动规划

2023 8th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2023-04-21 DOI: 10.1109/ICCRE57112.2023.10155579

Jacinto Colan, Ana Davila, Y. Hasegawa

引用次数: 0

A Bi-LSTM and AutoEncoder Based Framework for Multi-step Flight Trajectory Prediction 基于Bi-LSTM和自编码器的多步飞行轨迹预测框架

2023 8th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2023-04-21 DOI: 10.1109/ICCRE57112.2023.10155614

Han Wu, Yan Liang, Bin Zhou, Hao Sun

{"title":"A Bi-LSTM and AutoEncoder Based Framework for Multi-step Flight Trajectory Prediction","authors":"Han Wu, Yan Liang, Bin Zhou, Hao Sun","doi":"10.1109/ICCRE57112.2023.10155614","DOIUrl":"https://doi.org/10.1109/ICCRE57112.2023.10155614","url":null,"abstract":"Trajectory prediction (TP) is a key component in the route planning for civil aircraft. Most existing methods obtain multi-step TP via iterating the one-step TP model, which generally generates large cumulative error due to deviate from the original evolutionary pattern. To improve the situation, this paper proposes a multi-step TP framework with three modules: the Bi-directional Long Short-Term Memory Network (Bi-LSTM) based multi-step TP module, AutoEncoder based multi-step TP module, and voting fusion module. In the Bi-LSTM based multi-step TP method, to avoid the forgetting of evolutionary characteristics, the Bi-LSTM is designed to directly extract the mapping relationship between input of historical trajectory fragments and output of multi-step labels via data-driven method. In the AutoEncoder based multi-step TP module, the Bi-LSTM is deigned to learn mapping relationship between the input and core evolutionary features from output labels extracted via the encoder, and then the decoder is adopted to reconstruct predictions by outputs from Bi-LSTM. Third, the voting method was used to fuse the per-dimension predictions from the above two modules and further to refine multi-step predictions. The proposed multi-step TP framework is applied to real flight trajectory prediction of civil aircraft and outperforms multiple deep learning methods in the terms of RMSE and MAE.","PeriodicalId":285164,"journal":{"name":"2023 8th International Conference on Control and Robotics Engineering (ICCRE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130024908","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}

引用次数: 1

Mobile Robot Model Predictive Control Approach: Case Study of an Irrigation Canal 移动机器人模型预测控制方法:以灌溉渠为例

2023 8th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2023-04-21 DOI: 10.1109/ICCRE57112.2023.10155573

Roza Ranjbar, Javier G. Martin, J. Maestre, L. Etienne, E. Duviella, E. Camacho

引用次数: 0