Intelligent visual servoing with extreme learning machine and fuzzy logic
作者：
Highlights：
• The pseudoinverse of the interaction matrix, appropriate gain assignment and FOV keeping problems of VS are considered.
• An intelligent IBVS system using extreme learning machine and fuzzy logic is proposed to solve these problems in a single system.
• Initial velocity continuity and increased manipulability with fast converge in velocity limits are provided.
• The classical and the proposed IBVS system are simulated under bad camera calibration and noise as practical disturbances.
• Redefined analytical VS metrics verified the achievements of the proposed system.
摘要
•The pseudoinverse of the interaction matrix, appropriate gain assignment and FOV keeping problems of VS are considered.•An intelligent IBVS system using extreme learning machine and fuzzy logic is proposed to solve these problems in a single system.•Initial velocity continuity and increased manipulability with fast converge in velocity limits are provided.•The classical and the proposed IBVS system are simulated under bad camera calibration and noise as practical disturbances.•Redefined analytical VS metrics verified the achievements of the proposed system.
论文关键词：Image-based visual servoing,Extreme learning machine,Fuzzy logic
论文评审过程：Received 12 March 2016, Revised 19 August 2016, Accepted 20 October 2016, Available online 21 October 2016, Version of Record 2 January 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.10.048
