Abstract
Being trajectory tracking key for safe mobile robot navigation, Fuzzy Logic (FL) has been useful in tackling uncertainty and imprecision to realize robust and smooth trajectory tracking. In this paper, we present the Z-number based Fuzzy Logic control for trajectory tracking of differential wheeled mobile robots. The unique point of our approach lies in the ability to encode constraint and reliability in multi-input and multi-output rules, whose antecedent universe considers only the instantaneous measurements of distance and the orientation gaps, and whose consequent universe is computed by the interpolative reasoning and the graded mean integration approach. As a consequence, not only our approach avoids the complexity of encoding error gradients, but also is advantageous to model versatile control rules able to cope with missing observations and noisy inducements on actuators. Our experiments using both physics-based simulations and real-world tests based on a Pioneer 3DX robot architecture have elucidated the superior efficacy and the feasibility of the proposed controller regarding accuracy, robustness, and smoothness compared to other well-known related frameworks such as Fuzzy Logic Type 1, Fuzzy Logic Type 2 and Fuzzy Logic with PID. Our results provide unique insights to realize generalizable algorithms aided by FL and Z-number towards robust trajectory tracking.
Highlights
The recent spread of technological advancements have led mobile robots into the increasingly influential role throughout business segments facing cutting-edge innovation, rising costs and deficit in labor, such us autonomous vehicles, agriculture, forestry, manufacturing, exploration and transportation [1], [2]
Our results demonstrate that our approach brings the overall improved performance in terms on accuracy, robustness and smoothness compared to the existing well-known frameworks relevant to trajectory tracking based on Fuzzy-Logic, and provides unique insights useful to realize control algorithms towards robust and generalizable trajectory tracking performance
We presented a Z-number based Fuzzy Logic (Z-FL) control scheme for trajectory tracking with rules encodes by the instantaneous measurements of both the (Euclidean) distance to target and the orientation gap
Summary
The recent spread of technological advancements have led mobile robots into the increasingly influential role throughout business segments facing cutting-edge innovation, rising costs and deficit in labor, such us autonomous vehicles, agriculture, forestry, manufacturing, exploration and transportation [1], [2]. We present a Z-number based Fuzzy Logic (Z-FL) trajectory tracking control scheme with rules modeling the multi-input and multi-output nature of mobile robots. To validate the efficacy and the robustness of the proposed controller, (1) we performed rigorous computational and real-world experiments using a physics-based simulation environment and a Pioneer 3DX mobile robot, (2) we evaluated the trajectory tracking performance by using relevant considerations on accuracy, and using trajectories with distinct curvature profiles and diverse levels of disturbance, and (3) we compared to the existing well-known frameworks based on Fuzzy Logic (FL): FL-Type 1, FL-Type 2 and FL with PID. Our results demonstrate that our approach brings the overall improved performance in terms on accuracy, robustness and smoothness compared to the existing well-known frameworks relevant to trajectory tracking based on Fuzzy-Logic, and provides unique insights useful to realize control algorithms towards robust and generalizable trajectory tracking performance.
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