Effect of compliance on morphological control of dynamic locomotion with HyQ

Urbain, Gabriel; Barasuol, Victor; Semini, Claudio; Dambre, Joni; wyffels, Francis

doi:10.1007/s10514-021-09974-9

Cited by 11 publications

(3 citation statements)

References 50 publications

(58 reference statements)

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“…This choice guarantees accurate and stable predictions in closed-loop. A discussion on the subject is out of the scope of this article and is carried in [31]. This study also investigates more scrupulously the influence of the body parameters on the complexity of the neural network and the locomotion performance.…”

Section: Reflex-based Neural Networkmentioning

confidence: 99%

Stance Control Inspired by Cerebellum Stabilizes Reflex-Based Locomotion on HyQ Robot

Urbain

Barasuol

Semini

et al. 2020

2020 IEEE International Conference on Robotics and Automation (ICRA)

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Advances in legged robotics are strongly rooted in animal observations. A clear illustration of this claim is the generalization of Central Pattern Generators (CPG), first identified in the cat spinal cord, to generate cyclic motion in robotic locomotion. Despite a global endorsement of this model, physiological and functional experiments in mammals have also indicated the presence of descending signals from the cerebellum, and reflex feedback from the lower limb sensory cells, that closely interact with CPGs. To this day, these interactions are not fully understood. In some studies, it was demonstrated that pure reflex-based locomotion in the absence of oscillatory signals could be achieved in realistic musculoskeletal simulation models or small compliant quadruped robots. At the same time, biological evidence has attested the functional role of the cerebellum for predictive control of balance and stance within mammals. In this paper, we promote both approaches and successfully apply reflex-based dynamic locomotion, coupled with a balance and gravity compensation mechanism, on the state-of-art HyQ robot. We discuss the importance of this stability module to ensure a correct foot lift-off and maintain a reliable gait. The robotic platform is further used to test two different architectural hypotheses inspired by the cerebellum. An analysis of experimental results demonstrates that the most biologically plausible alternative also leads to better results for robust locomotion.

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Section: Reflex-based Neural Networkmentioning

confidence: 99%

Stance Control Inspired by Cerebellum Stabilizes Reflex-Based Locomotion on HyQ Robot

Urbain

Barasuol

Semini

et al. 2020

2020 IEEE International Conference on Robotics and Automation (ICRA)

Self Cite

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“…A promising alternative is to use general-purpose physics simulators, as they do not require the manual definition of a problem-specific mathematical model. 20 General-purpose physics simulators allow rapid evaluations of arbitrary structures and tasks with ad hoc quality metrics. 21 Consequently, they have served as the main backbone for many powerful robotic design optimization methodologies, such as the ones employed in evolutionary robotics.…”

Section: Introductionmentioning

confidence: 99%

Minimizing torque requirements in robotic manipulation through elastic elements optimization in a physics engine

Marchal,

Marzougui,

Furnémont

et al. 2024

International Journal of Advanced Robotic Systems

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The increasing number of robots and the rising cost of electricity have spurred research into energy-reducing concepts in robotics. One such concept, elastic actuation, introduces compliant elements such as springs into the robot structure. This article presents a comparative analysis between two types of elastic actuation, namely, monoarticular parallel elastic actuation and biarticular parallel elastic actuation, and demonstrates an end-to-end pipeline for their optimization. Starting from the real-world system identification of an RRR robotic arm, we calibrate a simulation model in a general-purpose physics engine and employ in silico evolutionary optimization to co-optimize spring configurations and trajectories for a pick-and-place task. Finally, we successfully transfer the in silico optimized elastic elements and trajectory to the real-world prototype. Our results substantiate the ability of elastic actuation to reduce the actuators’ torque requirements heavily. In contrast to previous work, we highlight the superior performance of the biarticular variant over the monoarticular configuration. Furthermore, we show that a combination of both proves most effective. This work provides valuable insights into the torque-reducing use of elastic actuation and demonstrates an actuator-invariant in silico optimization methodology capable of bridging the sim2real gap.

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“…In this regard, embedding compliance into the leg's structure has proved beneficial as springs contribute to impact absorption and energy return [4]. Moreover, springy legs also help to stabilize the motion [5], therefore becoming of paramount importance in dynamically stable locomotion [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Articulated legs allow energy optimization across different speeds for legged robots with elastically suspended loads

Astolfi

2023

2023 IEEE International Conference on Soft Robotics (RoboSoft)

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Legged robots are a promising technology whose use is limited by their high energy consumption. Biological and biomechanical studies have shown that the vibration generated by elastically suspended masses provides an energy advantage over rigidly carrying the same load. The robotic validation of these findings has only scarcely been explored in the dynamic walking case. In this context, a relationship has emerged between the design parameters and the actuation that generates the optimal gait. Although very relevant, these studies lack a generalizable analysis of different locomotion modes and a possible strategy to obtain optimal locomotion at different speeds. To this end, we propose the use of articulated legs in an extended Spring-Loaded Inverted Pendulum (SLIP) model with an elastically suspended mass. Thanks to this model, we show how stiffness and damping can be modulated through articulated legs by selecting the knee angle at touch-down. Therefore, by choosing different body postures, it is possible to vary the control parameters and reach different energetically optimal speeds. At the same time, this modeling allows the study of the stability of the defined system. The results show how suitable control choices reduce energy expenditure by 16% at the limit cycle at a chosen speed. The demonstrated strategy could be used in the design and control of legged robots where energy consumption would be dynamically optimal and usage time would be significantly increased.

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Effect of compliance on morphological control of dynamic locomotion with HyQ

Cited by 11 publications

References 50 publications

Stance Control Inspired by Cerebellum Stabilizes Reflex-Based Locomotion on HyQ Robot

Stance Control Inspired by Cerebellum Stabilizes Reflex-Based Locomotion on HyQ Robot

Minimizing torque requirements in robotic manipulation through elastic elements optimization in a physics engine

Articulated legs allow energy optimization across different speeds for legged robots with elastically suspended loads

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