Cognitive Robotics最新文献_第6页

Generative artificial intelligence in the metaverse era 元宇宙时代的生成人工智能

Cognitive Robotics Pub Date : 2023-01-01 DOI: 10.1016/j.cogr.2023.06.001

Zhihan Lv

引用次数: 10

LP-BT: A location privacy protection algorithm based on ball trees LP-BT:基于球树的位置隐私保护算法

Cognitive Robotics Pub Date : 2023-01-01 DOI: 10.1016/j.cogr.2023.05.001

Lechan Yang , Song Deng

{"title":"LP-BT: A location privacy protection algorithm based on ball trees","authors":"Lechan Yang , Song Deng","doi":"10.1016/j.cogr.2023.05.001","DOIUrl":"https://doi.org/10.1016/j.cogr.2023.05.001","url":null,"abstract":"<div><p>With the maturity of global positioning technology and the massive popularity of mobile terminals, location-based services can provide people with convenient and efficient assistance. To use such services, mobile users need to provide location information and request query content. However, this process inevitably leads to the leakage of users’ privacy information, which poses a great threat to their property and personal safety. To address the privacy leakage in location services, this paper proposes a location privacy protection method based on ball tree (LP-BT). We first use the ball tree as a spatial index structure, and then do fuzzification on the location information of end users to obtain the maximum primary anonymous entropy, and combine the neural network learning algorithm to predict the corresponding entropy value. Finally, the final entropy is obtained based on the average entropy of the two stages. Experimental results on public dataset manifest that our model is superior to other models such as random selection model and path-based fake location generation model in terms of privacy protection level, user density and anonymization time overhead.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"3 ","pages":"Pages 127-134"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49732906","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

Optimization of energy consumption in industrial robots, a review 工业机器人能耗优化研究综述

Cognitive Robotics Pub Date : 2023-01-01 DOI: 10.1016/j.cogr.2023.05.003

Mohsen Soori , Behrooz Arezoo , Roza Dastres

{"title":"Optimization of energy consumption in industrial robots, a review","authors":"Mohsen Soori , Behrooz Arezoo , Roza Dastres","doi":"10.1016/j.cogr.2023.05.003","DOIUrl":"https://doi.org/10.1016/j.cogr.2023.05.003","url":null,"abstract":"<div><p>Optimization of energy consumption in industrial robots can reduce operating costs, improve performance and increase the lifespan of the robot during part manufacturing. Choosing energy-efficient components such as motors, drives, and controllers can significantly reduce energy consumption in industrial robots. Over-sized motors and heavy robot arms can waste energy and decrease efficiency of industrial robots. By optimizing the robot programs and reducing idle time in robot operations, the amount of spent time can be reduced to minimize energy consumption of industrial robots. By using energy-efficient motors and drives, the amount of energy consumed by the robot can be reduced. Also, regular maintenance can reduce energy consumption of industrial robots by providing maximum efficiency for the robot's components. By implementing energy management systems, energy consumption of industrial robot can be monitored and analyzed to optimize energy consumption of industrial robot during working conditions. To minimize lost energy and reuse the energy usage during working times, regenerative braking can be used in the robots. The process of part manufacturing can be optimized in order to minimize the robot's movements and energy usage during working times of industrial robots. To analyze and optimize energy consumption in working schedules of industrial robots, different methodologies from recent published papers are reviewed in the study. Proper robot selection, energy-efficient robot motor and low wight robot arms, efficient programming of working schedules, regenerative braking system, regular maintenance of robot elements and optimized process of part production regarding the minimization of energy usage are discussed to optimize the energy consumption in industrial robots. As a result, future research works in the research field can be presented in order to optimize energy consumption, reduce operational costs, and increase sustainability of industrial robot operations in terms of productivity enhancement of part manufacturing.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"3 ","pages":"Pages 142-157"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49710401","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: 5

Co-attention learning cross time and frequency domains for fault diagnosis 跨时频域的故障诊断共注意学习

Cognitive Robotics Pub Date : 2023-01-01 DOI: 10.1016/j.cogr.2023.03.001

Ping Luo , Xinsheng Zhang , Ran Meng

引用次数: 0

Adjustable Convergence Rate Prescribed Performance with Fractional-Order PID Controller for Servo Pneumatic Actuated Robot Positioning 基于分数阶PID控制器的伺服气动机器人定位可调收敛速率规定性能

Cognitive Robotics Pub Date : 2023-01-01 DOI: 10.1016/j.cogr.2023.04.004

Mohd Iskandar Putra Azahar, Addie Irawan, R.M.T. Raja Ismail

{"title":"Adjustable Convergence Rate Prescribed Performance with Fractional-Order PID Controller for Servo Pneumatic Actuated Robot Positioning","authors":"Mohd Iskandar Putra Azahar, Addie Irawan, R.M.T. Raja Ismail","doi":"10.1016/j.cogr.2023.04.004","DOIUrl":"https://doi.org/10.1016/j.cogr.2023.04.004","url":null,"abstract":"<div><p>This study presents the method for optimal error tracking in position control for a servo pneumatic actuated robot grasper system using a new adjustable convergence rate prescribed performance control (ACR-PPC). It focuses on improving the feedback controller and the fractional-order proportional-integral-derivative (FOPID) controller used for the position control of each robot's finger. Multiple features were considered such as tracking error, rising time, faster transient response with finite-time convergence, oscillation reduction, and pressure stabilization in the pneumatic system. Experiments were conducted using a single finger of a tri-finger pneumatic gripper (TPG) robot, actuated by a single proportional valve with a double-acting cylinder (PPVDC). Two types of input trajectories were tested: step and sine wave inputs, which are common and critical for pneumatic systems. The results show that the proposed method eliminates oscillation and achieves high tracking performance within the prescribed bounds and minimal overshoot as well. The oscillation was suppressed with minimal overshoot and fast response was achieved by tuning the formulated adjustable prescribe performance function, thus improving the rising time response without significant loss of performance.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"3 ","pages":"Pages 93-106"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49732631","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

A colorization method for historical videos 一种历史视频的着色方法

Cognitive Robotics Pub Date : 2023-01-01 DOI: 10.1016/j.cogr.2023.07.001

Xin Jin, Yiqing Rong, Ke Liu, Chaoen Xiao, Xiaokun Zhang

引用次数: 0

Selection of PSO parameters based on Taguchi design-ANOVA- ANN methodology for missile gliding trajectory optimization 基于田口设计的导弹滑翔轨迹优化粒子群算法参数选择

Cognitive Robotics Pub Date : 2023-01-01 DOI: 10.1016/j.cogr.2023.05.002

Shubhashree Sahoo , Rabindra Kumar Dalei , Subhendu Kumar Rath , Uttam Kumar Sahu

{"title":"Selection of PSO parameters based on Taguchi design-ANOVA- ANN methodology for missile gliding trajectory optimization","authors":"Shubhashree Sahoo , Rabindra Kumar Dalei , Subhendu Kumar Rath , Uttam Kumar Sahu","doi":"10.1016/j.cogr.2023.05.002","DOIUrl":"https://doi.org/10.1016/j.cogr.2023.05.002","url":null,"abstract":"<div><p>The proposed research deals with selection of particle swarm optimization (PSO) algorithm parameters for missile gliding trajectory optimization relying on Taguchi design of experiments, analysis of variance (ANOVA) and artificial neural networks (ANN). Population size, inertial weight and acceleration coefficients of PSO were chosen for the present study. The experiments have been designed as per Taguchi's design of experiments using L<sub>25</sub> orthogonal array for selection of better PSO parameters. Missile gliding trajectory is optimized by discretizing angle of attack as control parameter, consequent conversion of optimal control problem to nonlinear programming problem (NLP) and finally solving the problem using PSO with optimized parameters to obtain optimum angle of attack and realization of maximum gliding range. Simulation results portrayed that the gliding range is maximized and missile glide distance is enhanced compared to earlier experiments. The efficiency of proposed approach was verified via different test scenarios.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"3 ","pages":"Pages 158-172"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49710728","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

Intelligent health management based on analysis of big data collected by wearable smart watch 基于可穿戴智能手表大数据分析的智能健康管理

Cognitive Robotics Pub Date : 2023-01-01 DOI: 10.1016/j.cogr.2022.12.003

CHEN Xiao-Yong , YANG Bo-Xiong , ZHAO Shuai , DING Jie , SUN Peng , GAN Lin Lindy

引用次数: 0

Safe reinforcement learning for high-speed autonomous racing 高速自动驾驶赛车的安全强化学习

Cognitive Robotics Pub Date : 2023-01-01 DOI: 10.1016/j.cogr.2023.04.002

Benjamin D. Evans, Hendrik W. Jordaan, Herman A. Engelbrecht

{"title":"Safe reinforcement learning for high-speed autonomous racing","authors":"Benjamin D. Evans, Hendrik W. Jordaan, Herman A. Engelbrecht","doi":"10.1016/j.cogr.2023.04.002","DOIUrl":"https://doi.org/10.1016/j.cogr.2023.04.002","url":null,"abstract":"<div><p>The conventional application of deep reinforcement learning (DRL) to autonomous racing requires the agent to crash during training, thus limiting training to simulation environments. Further, many DRL approaches still exhibit high crash rates after training, making them infeasible for real-world use. This paper addresses the problem of safely training DRL agents for autonomous racing. Firstly, we present a Viability Theory-based supervisor that ensures the vehicle does not crash and remains within the friction limit while maintaining recursive feasibility. Secondly, we use the supervisor to ensure the vehicle does not crash during the training of DRL agents for high-speed racing. The evaluation in the open-source F1Tenth simulator demonstrates that our safety system can ensure the safety of a worst-case scenario planner on four test maps up to speeds of 6 m/s. Training agents to race with the supervisor significantly improves sample efficiency, requiring only 10,000 steps. Our learning formulation leads to learning more conservative, safer policies with slower lap times and a higher success rate, resulting in our method being feasible for physical vehicle racing. Enabling DRL agents to learn to race without ever crashing is a step towards using DRL on physical vehicles.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"3 ","pages":"Pages 107-126"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49732926","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

Review on lane detection and related methods 车道检测及相关方法综述

Cognitive Robotics Pub Date : 2023-01-01 DOI: 10.1016/j.cogr.2023.05.004

Weiyu Hao

引用次数: 0