Smooth velocity tracking and kinematic-based fuzzy control of carrying mobile robots
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Smooth velocity tracking and kinematic‑based fuzzy control of carrying mobile robots Elham Almodarresi1 Received: 13 July 2020 / Accepted: 11 November 2020 © Springer Nature Switzerland AG 2020
Abstract Mobile robots are affected by forces imposed on them because of moving. These forces significantly affect the carrying efficiency of robots. In this study, the velocity profile is designed such that no extremum emerges on the rising and falling phases of the graph while a constant velocity is preserved between these parts. Decreasing the motion forces on the robot is the main goal of this study. In the second part of this study, a kinematic-based approach is presented to design fuzzy control rules. The significance of this approach is that unlike the methods proposed in the literature, in this method, the rate change of posture error is not required to enter into the fuzzy logic to provide the velocity tracking. This considerably reduces the computational effort with a decrease in the number of rules. In this method, proper indicators are defined as weights of the input and output linguistic functions of the fuzzy logic. Then, the inverse kinematics is employed to compute the proper weights of inputs based on each possible combination of outputs weights. Keywords Carrying mobile robot · Smooth velocity · Inverse kinematics · Fuzzy control
1 Introduction After perception and localization, the main step in controlling an autonomous drive robot is trajectory planning. A trajectory planning involves two parts: path planning and velocity planning. A general overview of recent path planning schemes, different categories, and approaches is presented in [1]. After designing the reference trajectory, an appropriate control strategy is required to track the trajectory. Fuzzy logics [2], PID tuning methods [3], sliding mode control [4], and a combination of them [5] are among common control strategies. The path planning problem is mostly studied in the literature, neglecting the reference velocity planning. This leads to an unsmooth trajectory tracking [6]. However, tracking the desired velocity is of high significance in carrying applications. The carrying mobile robots are widely exploited in health care, agriculture, food preparation, manufacturing, and military industries. An example
of using this technology is the food delivery navigation system [7] and robots carrying the medical rehabilitation devices [8]. It is important to prevent the packages from being exposed to motion forces when carrying food or liquid. To this end, the desired scenario here is to maintain a constant velocity in most of the route. The fuzzy logic method is then exploited to control the mobile robot. It provides the desired control characteristics just by interpreting demanded features to proper logic rules. Few previous works are dedicated to designing the proper fuzzy logics that guarantee velocity tracking. In this regard, the velocity tracking feature has been investigated in specific applications like food delivery robots [7], robots car
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