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Robots are moving towards applications in less structured environments, buttheir model-based controllers are challenged by the tasks' complexity andintrinsic environmental unpredictability. Studying biological motor control canprovide insights into overcoming these limitations due to the high dexterityand stability observable in humans and animals. This work presents ageometrical solution to the postural optimisation of 7-DoF limbs-likemechanisms, which are robust to singularities and computationally efficient.The theoretical formulation identified two separate decoupled optimisationstrategies. The shoulder and elbow strategy align the plane of motion with theexpected plane of motion and guarantee the reachability of the end-posture. Thewrist strategy ensures the end-effector orientation, which is essential toretain manipulability when nearing a singular configuration. The numericalresults confirmed the theoretical observations and allowed us to identify theeffect of different grasp strategies on system manipulability. The geometricalmethod was numerically tested in thousands of configurations proving to be bothrobust and accurate. The tested scenarios include left and right arm postures,singular configurations, and walking scenarios. The proposed geometricalapproach can find application in developing efficient and robust interactioncontrollers that could be applied in computational neuroscience and robotics.

Geometrical Postural Optimisation of 7-DoF Limb-Like Manipulators