###### Abstract  
Robotised Non Destructive Testing (NDT) presents multifaceted advantages, saving time and reducing repetitive manual workloads for highly skilled Ultrasonic Testing (UT) operators. Due to the requisite accuracy and reliability of the field, robotic NDT has traditionally relied on digital twins for complex path planning procedures enabling precise deployment of NDT equipment. This paper presents a multi-scale and collision-free path planning and implementation methodology enabling rapid deployment of robotised NDT with commercially available sensors. Novel algorithms are developed to plan paths over noisy and incomplete point clouds from low-cost sensors without the need for surface primitives. Further novelty is introduced in online path corrections utilising laser and force feedback while applying a Conformable-Wedge probe UT sensor. Finally, a novel source of data beneficial to automated NDT is introduced by collecting frictional forces of the surface informing the operator of the surface preparation quality. The culmination of this work is a new path-planning free, single-shot automated process removing the need for complex operator-driven procedures with a known surface, visualising collected data for the operator as a three-dimensional C-scan model. The dynamic robotic control enables a move to the industry 4.0 model of adaptive online path planning. Experimental results indicate the flexible and streamlined pipeline for robotic deployment, and demonstrate intuitive data visualisation to aid highly skilled operators in a wide field of industries. NDT; free form surface profiling; flexible automatised robotic systems; Ultrasonic Testing; remanufacture 202212528. 202220223 May 20223 May 20223 May 2022  
becoming prevalent within NDT. Despite this, many issues with map reconstruction still prove to be a critical block to more general usage within robotised NDT. An initial study of 2D Visual Odometry and part mosaicing [4] highlighted several drawbacks with visual imaging and NDT. The key block to wide-spread usage is that highly specular surfaces such as polished metal produce significant visual artefacts. For sectors such as remanufacturing and aerospace that rely on polished metal or highly reflective Carbon-Fibre Reinforced Polymer (CFRP) samples, this is a critical issue. A related work found that a robotically applied Structure-from-Motion (SfM) schema could reproduce parts with sub-millimetre accuracy once the point clouds had been processed [5]. Key to this method is the presence of significant visual artefacts on the part, allowing dense point-cloud extraction from subsequent 2D images taken at known positions. These studies have presented significant improvements in reverse engineering of parts for later NDT scanning. However, the scans taken for these parts are completed by two complex robotic procedures that are operator-specified. The operator must input a path that is known not to either collide with the part or meet kinematic singularities, and is entirely reachable by the robot. In order to construct a dense 3D map of the part, the data threshold is high, requiring hundreds of images with up to 85% image overlap to ensure proper part-reconstruction. This presents the significant disadvantage of requiring the part to be stationary within the cell while camera and UT probe tools are interchanged, since the derived CAD model is localised with respect to the robotic work-space. Small one-shot surface profiling systems such as RGB/D or LIDAR cameras present solutions to this problem, able to profile the surface with the UT probe attached. Several autonomous robotic arm [6; 7] and drone based [8] NDT scanning methods rely on this approach. The key drawback of these deployments are the reliance on primitives such as cylinders and planes, reducing flexibility when faced with complex, warped or unknown surfaces. The authors have used the raw point cloud data from off-the-shelf RGB/D cameras to construct paths over the surface, complimented by online path corrections during the UT scan.