The Path Planning and Location Method of Inspection Robot in a Large Storage Tank Bottom

Abstract

With the development of robot technology, inspection robots have been applied to the defect detection of large tanks. However, the existing path planning algorithm of the tank bottom detection robot is easy to fall into the local minimum, and the path is not smooth. Besides, the positioning of the tank bottom detection robot is not accurate. This article proposes a path planning and location algorithm for the large tank bottom detection robot. Specifically, we design a preset spiral path according to the shape of the tank bottom, and a rotating potential field (RPF) near the obstacle is added to avoid the problem of path planning falling into a local minimum. We obtained accurate and smooth planning results. Compared with the state-of-the-art, the RPF method reduced the average RMSE by 9.49%. In addition, by measuring the acoustic emission distance, the three-point positioning algorithm can be used to achieve the calculation of the robot position detection in the proposed method, and the average positioning error on the spiral path is only 0.0748 ± 0.0032.

A Pre-Grasping Motion Planning Method Based on Improved Artificial Potential Field for Continuum Robots

“…Linjia Hao tackled the local minimum and unreachable issues with an improved APF, including the piecewise repulsion function and dynamic gravitational constant [59]. Yinchu Wang prevented the robot from getting trapped in the local extrema and deviating from the desired path by introducing a rotating potential field near obstacles [60]. For whole-arm grasping using CRs with force closure grasps, a specific grasping point is unnecessary, as the CR merely needs to conform to the target's shape to achieve force closure.…”