Computational design of a quadroped: an algorithm for optimizing rotary drive parameters

An algorithm of computational design for finding optimal parameters for rotary drives of locomotion robots that meet performance and behavioral requirements, is presented. Anthropomorphic robots, quadrupeds, and so-called general-purpose robots are equipped with pedipulatory mechanisms for navigating unstructured and a priori unknown environments. The requirements imposed on the mechanisms in terms of load capacity, dynamics, energy efficiency, safety and aesthetics may contradict each other. For example, aesthetics involves minimizing the overall dimensions of the drives, the load capacity requires an increase in gear ratio, and this increases reflected inertia and friction losses, adversely affecting dynamics and energy efficiency. In the external cycle of the proposed algorithm, the optimal parameters of rotary drives are searched for by the total weight and gear ratio of the drives. Regression models trained on the passport data of commercial drives recover key parameters such as nominal and peak torques, reflected inertia, motor constant, estimated overall dimensions of the drives and the efficiency of the gearbox. In the internal cycle of the proposed algorithm, the trajectory optimization problem is solved for a complete model of robot dynamics with limitations on torque, velocity, kinematics and contacts by estimating energy through an electrical model with separation of electrical losses and friction losses. The proposed algorithm is tested to solve the problem of designing a quadroped. The algorithm’s input data include behavioral characteristics (walking, dynamic movements such as jumping) and performance parameters (for example, when handling a payload). The algorithm’s output is a set of physical parameter estimates sufficient for design considerations. Verification of the parameters is performed using simulation tools.

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