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Improved Energy Efficiency via Parallel Elastic Elements for the Straight-Legged Vertically-Compliant Robot SLIDER

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Abstract

Most state-of-the-art bipedal robots are designed to be anthropomorphic, and therefore possess articulated legs with knees. Whilst this facilitates smoother, human-like locomotion, there are implementation issues that make walking with straight legs difficult. Many robots have to move with a constant bend in the legs to avoid a singularity occurring at the knee joints. The actuators must constantly work to maintain this stance, which can result in the negation of energy-saving techniques employed. Furthermore, vertical compliance disappears when the leg is straight and the robot undergoes high-energy loss events such as impacts from running and jumping, as the impact force travels through the fully extended joints to the hips. In this paper, we attempt to improve energy efficiency in a simple yet effective way: attaching bungee cords as elastic elements in parallel to the legs of a novel, knee-less biped robot SLIDER, and show that the robot’s prismatic hip joints preserve vertical compliance despite the legs being constantly straight. Due to the nonlinear dynamics of the bungee cords and various sources of friction, Bayesian Optimization is utilized to find the optimals configuration of bungee cords that achieves the largest reduction in energy consumption. The optimal solution found saves 15% of the energy consumption compared to the robot configuration without parallel elastic elements. Additional Video: https://youtu.be/ZTaG9_-Dz8A

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Notes

  1. 1.

    Due to the COVID-19 pandemic, access to the physical robot has been limited. We thus focus on validating the concept and do not focus on whole-body walking experiments.

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Correspondence to Ke Wang .

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Wang, K., Saputra, R.P., Foster, J.P., Kormushev, P. (2022). Improved Energy Efficiency via Parallel Elastic Elements for the Straight-Legged Vertically-Compliant Robot SLIDER. In: Chugo, D., Tokhi, M.O., Silva, M.F., Nakamura, T., Goher, K. (eds) Robotics for Sustainable Future. CLAWAR 2021. Lecture Notes in Networks and Systems, vol 324. Springer, Cham. https://doi.org/10.1007/978-3-030-86294-7_12

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