Reconfiguration of Modular Hyper-Redundant Manipulators via Normalised Manipulability, Workspace Density, and Workspace Volume Percentage Indices

In recent decades, the demand for service robotics has increased in different applications. In particular, inspection and maintenance tasks require to operate in hazardous, dan-gerous, or inaccessible areas where robots can safely operate. In this context, thanks to their ability to move in hazardous and constrained environments, hyper-redundant manipulators represent an effective solution. Typically, the design of specific devices is required to accomplish inspection and maintenance tasks. Thus, changes in the working environment imply the necessity of designing new customised devices, increasing the production cost and time. A possible solution is to design a reconfigurable hyper-redundant manipulator that can adapt its structure to have high performance in different tasks. This paper proposes a novel method to find the assembly configuration of a modular hyper-redundant manipulator exploiting the Normalised Manipulability, Workspace Density, and Workspace Volume percentage indices. The proposed algorithm performs a multi-variable analysis based on these indices to select the non-dominated assembly configurations to perform a desired task. The proposed algorithm is implemented using an exemplary modular reconfigurable hyper-redundant manipulator to verify the feasibility of the proposed method.