Robot vision system based on information visualization algorithm

Xu, Hui

doi:10.1007/s13198-021-01515-y

Cited by 2 publications

(2 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Zhao et al [24] developed a GM (1,1) model to predict WEEE in China based on home appliance ownership. Xu et al [25] designed a prediction model combining the GM (1,1) model and FTS model to forecast electronics recycling. Wang et al [11] proposed a decomposition-integrated hybrid forecasting method integrating the variable mode decomposition (VMD) and exponential smoothing model (ESM) in the grey model (GM) for WEEE quantity forecasting.…”

Section: Related Research On Weee Recycling Predictionmentioning

confidence: 99%

Prediction of WEEE Recycling in China Based on an Improved Grey Prediction Model

Xiao

Wang

2022

Sustainability

View full text Add to dashboard Cite

Accurate waste electrical and electronic equipment (WEEE) recycling forecast is an essential reference for optimizing e-waste industry layout and division of labor policies, conducive to better guiding enterprises’ recycling activities and improving the efficiency of WEEE recycling in China. The nonlinear grey Bernoulli model (NGBM (1,1)) was constructed by analyzing the recycling data characteristics of WEEE from 2012 to 2020, and a particle swarm optimization (PSO) algorithm was introduced to solve the model parameters and optimize the background value coefficients. The prediction results were compared with other grey prediction models to verify the effectiveness of the improved NGBM (1,1) model for WEEE recycling prediction in China and the applicability of the PSO algorithm for improving the prediction accuracy of each grey model. Statistical data were used to forecast the WEEE recycling volume in China from 2021 to 2023, and the results show that the value of WEEE recycling will continue to grow at 9%. The value of recycling will reach 16 billion yuan by 2023, while the value of WEEE recycling will see a slight decline. Based on the calculation results, the WEEE recycling industry development trend is predicted to guide the promotion of the WEEE industry recycling program and the national circular economy program.

show abstract

Section: Related Research On Weee Recycling Predictionmentioning

confidence: 99%

Prediction of WEEE Recycling in China Based on an Improved Grey Prediction Model

Xiao

Wang

2022

Sustainability

View full text Add to dashboard Cite

show abstract

“…Therefore, ensuring the safety of the visual servo algorithm is of utmost importance. The main cause of collisions lies in the uncertainty of the relative motion between the manipulator and the target due to external disturbances [ 2 ]. Analyzing the visual servo process from a kinematic perspective reveals that the manipulator’s motion trajectory is influenced by the target’s uncertain motion trajectory.…”

Section: Introductionmentioning

confidence: 99%

A High-Certainty Visual Servo Control Method for a Space Manipulator with Flexible Joints

Yang

Zhao³

et al. 2023

Sensors

View full text Add to dashboard Cite

This paper introduces a novel high-certainty visual servo algorithm for a space manipulator with flexible joints, which consists of a kinematic motion planner and a Lyapunov dynamics model reference adaptive controller. To enhance kinematic certainty, a three-stage motion planner is proposed in Cartesian space to control the intermediate states and minimize the relative position error between the manipulator and the target. Moreover, a planner in joint space based on the fast gradient descent algorithm is proposed to optimize the joint’s deviation from the centrality. To improve dynamic certainty, an adaptive control algorithm based on Lyapunov stability analysis is used to enhance the system’s anti-disturbance capability. As to the basic PBVS (position-based visual servo methods) algorithm, the proposed method aims to increase the certainty of the intermediate states to avoid collision. A physical experiment is designed to validate the effectiveness of the algorithm. The experiment shows that the visual servo motion state in Cartesian space is basically consistent with the planned three-stage motion state, the average joint deviation index from the centrality is less than 40%, and the motion trajectory consistency exceeds 90% under different inertial load disturbances. Overall, this method reduces the risk of collision by enhancing the certainty of the basic PBVS algorithm.

show abstract

Robot vision system based on information visualization algorithm

Cited by 2 publications

References 18 publications

Prediction of WEEE Recycling in China Based on an Improved Grey Prediction Model

Prediction of WEEE Recycling in China Based on an Improved Grey Prediction Model

A High-Certainty Visual Servo Control Method for a Space Manipulator with Flexible Joints

Contact Info

Product

Resources

About