Investigation of a non-anthropomorphic bipedal robot with stability, agility, and simplicity

Yu, Jeffrey; Hooks, Joshua; Ghassemi, Sepehr; Pogue, Alexandra; Hong, Dennis

doi:10.1109/urai.2016.7734010

Cited by 8 publications

(1 citation statement)

References 11 publications

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“…Sideways walking has been studied in a relatively smaller number of robots. One important exception in bipeds [49] shows that rotating the hips and knees to operate in the sagittal plane with a nonanthropomorphic gait is akin to walking sideways and reduces roll oscillations [50]. In this design, adding rotation at the hip is best for steering, resulting in a biped leg design that is similar to a crab leg [51].…”

Section: Introductionmentioning

confidence: 99%

Sideways crab-walking is faster and more efficient than forward walking for a hexapod robot

et al. 2022

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Articulated legs enable the selection of robot gaits, including walking in different directions such as forward or sideways. For longer distances, the best gaits might maximize velocity or minimize the cost of transport (COT). Interestingly, while animals often adapt their morphology for walking either forward (like insects) or sideways (like crabs), robots that can walk forward or sideways often pick a direction by convention. In this paper, we compare walking in forward and sideways directions. To do this, a simple gait design method is introduced for determining forward and sideways gaits with equivalent body heights and step heights. Specifically, the frequency and stride lengths are tuned within reasonable constraints to find gaits that represent a robot’s performance potential in terms of speed and energy cost. Experiments are performed in both dynamic simulation in Webots and a laboratory environment with our 18 degree-of-freedom (DOF) hexapod robot, Sebastian. With the common three joint leg design, the results show that sideways walking is overall better (75% larger walking speed and 40% lower COT). The performance of sideways walking was better on both hard floors and granular media (dry play sand). This supports the development of future crab-like walking robots for future applications. In future work, this approach may be used to develop nominal gaits without extensive optimization, and to explore whether the advantages of sideways walking persist for other hexapod designs.

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Section: Introductionmentioning

confidence: 99%

Sideways crab-walking is faster and more efficient than forward walking for a hexapod robot

et al. 2022

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Legged Robots, Design of

Hong¹,

Ahn²,

Hooks³

et al. 2020

Encyclopedia of Robotics

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A Proprioceptive, Force-Controlled, Non-Anthropomorphic Biped for Dynamic Locomotion

Hooks

Zhang

et al. 2018

2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)

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This paper addresses the challenge of terrainadaptive dynamic locomotion in humanoid robots, a problem traditionally tackled by optimization-based methods or reinforcement learning (RL). Optimization-based methods, such as model-predictive control, excel in finding optimal reaction forces and achieving agile locomotion, especially in quadruped, but struggle with the nonlinear hybrid dynamics of legged systems and the real-time computation of step location, timing, and reaction forces. Conversely, RL-based methods show promise in navigating dynamic and rough terrains but are limited by their extensive data requirements. We introduce a novel locomotion architecture that integrates a neural network policy, trained through RL in simplified environments, with a state-of-the-art motion controller combining model-predictive control (MPC) and whole-body impulse control (WBIC). The policy efficiently learns high-level locomotion strategies, such as gait selection and step positioning, without the need for full dynamics simulations. This control architecture enables humanoid robots to dynamically navigate discrete terrains, making strategic locomotion decisions (e.g., walking, jumping, and leaping) based on ground height maps. Our results demonstrate that this integrated control architecture achieves dynamic locomotion with significantly fewer training samples than conventional RLbased methods and can be transferred to different humanoid platforms without additional training. The control architecture has been extensively tested in dynamic simulations, accomplishing terrain height-based dynamic locomotion for three different robots.

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Investigation of a non-anthropomorphic bipedal robot with stability, agility, and simplicity

Cited by 8 publications

References 11 publications

Sideways crab-walking is faster and more efficient than forward walking for a hexapod robot

Sideways crab-walking is faster and more efficient than forward walking for a hexapod robot

Legged Robots, Design of

A Proprioceptive, Force-Controlled, Non-Anthropomorphic Biped for Dynamic Locomotion

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