Fuzzy-PID hybrid controller for mobile robot using point cloud and low cost depth sensor

Salhi, Khaled; Alimi, Adel M.

doi:10.1109/icbr.2013.6729280

Cited by 7 publications

(2 citation statements)

References 12 publications

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“…Applications of the fuzzy system are useful in every field of life like Cognitive Science, Robotics, Industry, Medical Field, Agriculture, Weather forecasting, etc. Fuzzy based simulation for attention mechanism in CR is performed to describe the level of attention required based on the type of motion and FE [32,33]. In this research, attention depends upon the selected values of FE and motion.…”

Section: Proposed Task Planning In Cloud Roboticsmentioning

confidence: 99%

Intelligent task planner for cloud robotics using level of attention empowered with fuzzy system

et al. 2020

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Cloud robotics is a field of robotics that endeavors to summon cloud advances, for instance, cloud computing, and other internet advances focused on the advantages of merged framework and shared administrations for robotics. In this research, an intelligent task planning mechanism is proposed to attain a certain level of attention for knowledge sharing among cloud-based robots using mamdani fuzzy inference system (MFIS). The proposed task planning mechanism using mamdani fuzzy inference system (TPM-MFIS), can classify the different stages of attention such as very high, high, medium, low, very low and none. In this recommended intelligent system, cloud robotics services are used to maintain the workload of each robot. Whereas, all fuzzification and decision-making policies handled on cloud to avoid the redundancy task planning consumption on individual level. This system has two input variables that are facial expression and motion rate. Input variables detect the output level of attention to be very high, high, medium, low, very low, and none. This paper presents an analysis of the result's accuracy using proposed TPM-MFIS to model the task planning process.

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Section: Proposed Task Planning In Cloud Roboticsmentioning

confidence: 99%

Intelligent task planner for cloud robotics using level of attention empowered with fuzzy system

et al. 2020

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“…In the work of Li et al, a trajectory tracking control for a mobile robot is proposed based on a self-adaptive fuzzy PID controller which use the path error and the heading error into the control closed loop to compute the control action ( Li, He, & Yin, 2012 ). In the work of Salhi and Alimi (2013 ) a similar idea is implemented using point cloud and low cost depth sensor. A fuzzy PI version is presented in the work of Sheikhlar, Fakharian, and Adhami-Mirhosseini (2013 ) where fuzzy inference rules were established by using the tracking error and its derivative.…”

Section: Related Workmentioning

confidence: 99%