<p>This research proposes an iterative linear quadratic regulator (iLQR) based navigation method for a wall-pressed crawler type in-pipe robots. In order to maintain traction forces pushing the track modules against the pipe wall, the robot actively adjusts its size. It also controls its track velocities to match the pipe axial direction for steady travel. The in-pipe robot’s relative position to the pipeline affects both maintaining appropriate traction and aligning the posture. An integrated controller utilizing iLQR is suggested because the problem cannot be effectively handled by linear control methods. The iLQR is suitable for real-time control systems for nonlinear systems due to its computational efficiency. To overcome spatial constraints and assess the performance of the proposed approach, simulation is used. Simulation results demonstrate that the suggested iLQR-based integrated control method effectively reduced power consumption of the track modules by approximately 45 %.</p>

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Driving method using optimal posture control of an inpipe robot

  • Jungwan Park

摘要

This research proposes an iterative linear quadratic regulator (iLQR) based navigation method for a wall-pressed crawler type in-pipe robots. In order to maintain traction forces pushing the track modules against the pipe wall, the robot actively adjusts its size. It also controls its track velocities to match the pipe axial direction for steady travel. The in-pipe robot’s relative position to the pipeline affects both maintaining appropriate traction and aligning the posture. An integrated controller utilizing iLQR is suggested because the problem cannot be effectively handled by linear control methods. The iLQR is suitable for real-time control systems for nonlinear systems due to its computational efficiency. To overcome spatial constraints and assess the performance of the proposed approach, simulation is used. Simulation results demonstrate that the suggested iLQR-based integrated control method effectively reduced power consumption of the track modules by approximately 45 %.