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The purpose of this paper is to develop a fundamental external-force-detection framework for construction manipulators. Such an industrial application demands the practicality that satisfies detection requirements such as the accuracy and robustness while ensuring (i) a low cost, (ii) wide applicability, and (iii) a simple detection algorithm. For satisfying (i) and (ii), our framework first adopts a hydraulic sensor as a force sensor. However, hydraulic-pressure readings essentially include error force components. These components depend strongly on the joint kinetic state and differ in the identification difficulty owing to a nonlinear and uncertain hydromechanical system. For satisfying (ii) and (iii), our framework thus focuses on the dominant error-force components classified by the control input states, such as self-weight, cylinder driving, and oscillating forces, and identifies and removes them by using a theoreticalmodel, an experimental estimation, and a waveform analysis without complex modeling, respectively. Experiments were conducted using an instrumented hydraulic arm system. The results of a no-load task indicate that our framework greatly lowers the threshold to determine the on-off state of external force application, independent of the joint kinetic states. The results of an on-load task confirm that our framework robustly identifies the off states in which an external force is not applied to the hydraulic cylinder.

Identification of Dominant Error Force Component in Hydraulic Pressure Reading for External Force Detection in Construction Manipulator