###### Abstract
An adaptive robotic system using a custom-developed 3D laser-triangulation profilometer was developed for the robotic deburring of die-cast parts with position and orientation error correction [27]. Through discrete event simulation and 3D digital human modeling, a multi-purpose digital simulation approach was proposed for the sustainability enhancement of a real manufacturing cell of the aerospace industry, automated by robotic deburring [28]. The current research and applications of robotic deburring are mainly carried out by one or more traditional and commercial six-degree-of-freedom (six-DOF) serial industrial robot manipulators, which are not always suitable for the robotic deburring of complex shaped parts with highly dexterous orientations adjustment and efficient multi-faces deburring in one setup because of the defective nature of this kind of serial robot manipulator, e.g., the weakened structural rigidity of the extended robot manipulator when it is reaching far deburring position with a cantilever-beam-like structure, and the poor accessibility and small safety margins between robot manipulator and workpiece resulting from its difficulties in both obstacle avoidance adjustment and deburring orientation adjustment. Several studies investigating tool path adaptation and process parameter control for robotic deburring were presented. A tool path adaptation for robotic deburring was presented in accordance with the registration using a custom 3D laser-triangulation profilometer to compensate the positioning errors of the currently processed workpiece, which is difficult to ensure repeatable clamping [27]. A tool path modification method based on a computer-aided design model and direct teaching was proposed to compensate for the position/orientation errors of the workpiece, in addition, impedance control was used to avoid applying an excessive contact force and a virtual wall was adopted to improve the force-control performance for the robotic deburring process [29]. An application of a human mimicking control strategy that mimics the human behavior during the manual deburring on the deburring of hard material items using an industrial robot was introduced [30]. By satisfying a set of constraints to properly perform the desired surface contact conditioning, a hybrid position/force control approach using task priority and sliding mode control was proposed for contact-driven robotic surface treatments such as deburring [31; 32]. A set of optimal process parameter combination for robotic machining and the effect of process parameters such as spindle speed, feed rate and tool path strategies on the performance characteristics were investigated using the Taguchi-Grey relational approach and analysis of variance [33]. Edge robotic deburring with a controlled force progression pneumatic tool, as well as a methodology used to select and optimize the edge robotic deburring process, was presented [25]. A sliding mode control method based on radial basis function neural network was proposed for the deburring of industry robotic systems, without the requirements for strict constraints, an accurate model and exact parameters [34]. A fuzzy proportional-integral-derivative (PID) control method for deburring industrial robots was proposed and the PID controller parameters can be updated online at each sampling time to allow adaptive compensation for error and guarantee trajectory accuracy of the end-effector [35]. A vision-based approach, a Pythagorean hodograph quintic spline interpolator based on S curve acceleration/deceleration and an integrated process control structure consisting of an adaptive disturbance compensator, a sliding mode controller, and a friction compensator were investigated for force control and contour following in industrial applications such as deburring [36]. These studies of tool path adaptation and process parameter control for robotic deburring are usually conducted on one or more traditional and commercial six-DOF serial industrial robot manipulators.