Balance Control of a Hexapod Robot Using Fuzzy Logic and Inverse Kinematics Algorithm with Real-Time IMU Sensor Measurement
Abstract
Robotic technology is a crucial pillar in modern civilization, especially in high-risk environments such as post-disaster evacuation scenarios. Hexapod legged robots are designed to navigate uneven terrains that are inaccessible to humans. Although hexapods offer superior mobility and flexibility, they face stability challenges when moving on inclined surfaces due to uneven load distribution, which can affect servo motor performance. To address this issue, this study implements a control system combining fuzzy logic and inverse kinematics to maintain body stability. An Inertial Measurement Unit (IMU) sensor is also integrated to detect the robot’s orientation angle in real-time, enabling adaptive posture correction. This research focuses on three main problems: first, how inverse kinematics can stabilize hexapod posture on sloped surfaces; second, how IMU sensors detect inclination and orientation; and third, how fuzzy logic control contributes to balance regulation. The methodology involves system design, experimental testing, and performance analysis based on the robot's body tilt measurements across various inclinations. The results show that the proposed system responds effectively to surface tilt, particularly in pitch angle correction and maintaining a neutral position. Inverse kinematics successfully calculates leg configurations to keep the body posture stable. The IMU sensor demonstrates high accuracy in angle detection, while fuzzy logic provides flexibility in decision-making for posture control. The integration of these three approaches proves effective in maintaining hexapod balance on inclined terrains, thus supporting their potential use in complex, unstable environments.
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References
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