Input Displacement Neuro-fuzzy Control and Object Recognition by Compliant Multi-fingered Passively Adaptive Robotic Gripper

@article{Petkovi2016InputDN,
  title={Input Displacement Neuro-fuzzy Control and Object Recognition by Compliant Multi-fingered Passively Adaptive Robotic Gripper},
  author={Dalibor Petkovi{\'c} and Shahaboddin Shamshirband and Nor Badrul Anuar and Aznul Qalid Md Sabri and Zulkanain Abdul Rahman and Nenad D. Pavlovic},
  journal={Journal of Intelligent \& Robotic Systems},
  year={2016},
  volume={82},
  pages={177-187}
}
The requirement for new flexible adaptive grippers is the ability to detect and recognize objects in their environments. It is known that robotic manipulators are highly nonlinear systems, and an accurate mathematical model is difficult to obtain, thus making it difficult make decision strategies using conventional techniques. Here, an adaptive neuro fuzzy inference system (ANFIS) for controlling input displacement and object recognition of a new adaptive compliant gripper is presented. The… 
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