On the Technological Instantiation of a Biomimetic Leg Concept for Agile Quadrupedal Locomotion

2015 ◽  
Vol 7 (3) ◽  
Author(s):  
Elena Garcia ◽  
Juan C. Arevalo ◽  
Manuel Cestari ◽  
Daniel Sanz-Merodio
Keyword(s):  
Experimental Evaluation ◽  
Complex Terrain ◽  
Legged Locomotion ◽  
Natural Environments ◽  
Quadrupedal Locomotion ◽  
Optimum Performance ◽  
Natural Complex ◽  
Quadruped Robots ◽  
Locomotion System ◽  
Leg Design

The legged locomotion system of biological quadrupeds has proven to be the most efficient in natural, complex terrain. Particularly, horses' legs have been evolved to provide speed, endurance, and strength superior to any other animal of equal size. Quadruped robots, emulating their biological counterparts, could become the best choice for field missions in complex or natural environments; however, they should be provided with optimum performance against mobility, payload, and endurance. The design of the leg mechanism is of paramount importance to achieve the targeted performance, and in order to design a leg mechanism able to provide the robot with such agile capabilities nature is the best source for inspiration. In this work, key principles underlying horse legs' power capabilities have been extracted and translated to a biomimetic leg concept. Afterwards, a real prototype has been designed following the biomimetic concept proposed. A key element in the biomimetic concept is the multifunctionality of the natural musculotendinous system, which has been mimicked by combining series elastic actuation and passive elements. This work provides an assessment of the benefits that bio-inspired solutions can provide versus the purely engineering approaches. The experimental evaluation of the bio-inspired prototype shows an improvement on the performance compared to a leg design based on purely engineering principles.

scholarly journals Learning quadrupedal locomotion over challenging terrain

2020 ◽  
Vol 5 (47) ◽  
pp. eabc5986 ◽  
Author(s):  
Joonho Lee ◽  
Jemin Hwangbo ◽  
Lorenz Wellhausen ◽  
Vladlen Koltun ◽  
Marco Hutter
Keyword(s):  
Neural Network ◽  
Reinforcement Learning ◽  
Legged Locomotion ◽  
Natural Environments ◽  
State Machines ◽  
Robust Controller ◽  
Locomotion Control ◽  
Animal Locomotion ◽  
Quadrupedal Locomotion ◽  
Motion Primitives

Legged locomotion can extend the operational domain of robots to some of the most challenging environments on Earth. However, conventional controllers for legged locomotion are based on elaborate state machines that explicitly trigger the execution of motion primitives and reflexes. These designs have increased in complexity but fallen short of the generality and robustness of animal locomotion. Here, we present a robust controller for blind quadrupedal locomotion in challenging natural environments. Our approach incorporates proprioceptive feedback in locomotion control and demonstrates zero-shot generalization from simulation to natural environments. The controller is trained by reinforcement learning in simulation. The controller is driven by a neural network policy that acts on a stream of proprioceptive signals. The controller retains its robustness under conditions that were never encountered during training: deformable terrains such as mud and snow, dynamic footholds such as rubble, and overground impediments such as thick vegetation and gushing water. The presented work indicates that robust locomotion in natural environments can be achieved by training in simple domains.

scholarly journals A Bio-Inspired Compliance Planning and Implementation Method for Hydraulically Actuated Quadruped Robots with Consideration of Ground Stiffness

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2838
Author(s):  
Xiaoxing Zhang ◽  
Haoyuan Yi ◽  
Junjun Liu ◽  
Qi Li ◽  
Xin Luo
Keyword(s):  
Harmonic Oscillation ◽  
Ground Surface ◽  
Legged Locomotion ◽  
Soft Ground ◽  
Quadruped Robots ◽  
In Series ◽  
Reaction Forces ◽  
Implementation Method ◽  
The Stability ◽  
Natural Dynamics

There has been a rising interest in compliant legged locomotion to improve the adaptability and energy efficiency of robots. However, few approaches can be generalized to soft ground due to the lack of consideration of the ground surface. When a robot locomotes on soft ground, the elastic robot legs and compressible ground surface are connected in series. The combined compliance of the leg and surface determines the natural dynamics of the whole system and affects the stability and efficiency of the robot. This paper proposes a bio-inspired leg compliance planning and implementation method with consideration of the ground surface. The ground stiffness is estimated based on analysis of ground reaction forces in the frequency domain, and the leg compliance is actively regulated during locomotion, adapting them to achieve harmonic oscillation. The leg compliance is planned on the condition of resonant movement which agrees with natural dynamics and facilitates rhythmicity and efficiency. The proposed method has been implemented on a hydraulic quadruped robot. The simulations and experimental results verified the effectiveness of our method.

Modelling and simulation of artificial locomotion systems

Robotica ◽  
2005 ◽  
Vol 23 (5) ◽  
pp. 595-606 ◽  
Author(s):  
Manuel F. Silva ◽  
J. A. Tenreiro Machado ◽  
António M. Lopes
Keyword(s):  
Simulation Model ◽  
Fractional Order ◽  
Soil Mechanics ◽  
Viscous Friction ◽  
Legged Locomotion ◽  
Modelling And Simulation ◽  
Locomotion System ◽  
Linear Spring ◽  
Robot Leg ◽  
Robot Body

This paper describes a simulation model for a multi-legged locomotion system with joints at the legs having viscous friction, flexibility and backlash. For that objective the robot prescribed motion is characterized in terms of several locomotion variables. Moreover, the robot body is divided into several segments in order to emulate the behaviour of an animal spine. The foot-ground interaction is modelled through a non-linear spring-dashpot system whose parameters are extracted from the studies on soil mechanics. To conclude, the performance of the developed simulation model is evaluated through a set of experiments while the robot leg joints are controlled using fractional order algorithms.

scholarly journals Design, Modeling, and Control of a Wheel-Legged Locomotion System for the Environmental Hybrid Robot

2011 ◽  
Author(s):  
Gustavo Freitas ◽  
Fernando Lizarralde ◽  
Liu Hsu ◽  
Vitor Paranhos ◽  
Ney R. Salvi dos Reis ◽  
...  
Keyword(s):  
Legged Locomotion ◽  
Modeling And Control ◽  
Locomotion System ◽  
And Control

Leg Design for Delivery Quadruped Robots Based on EMA and Energy Optimization

2021 ◽  
pp. 771-780
Author(s):  
Haoyuan Yi ◽  
Zhenyu Xu ◽  
Liming Zhou ◽  
Xin Luo
Keyword(s):  
Energy Optimization ◽  
Quadruped Robots ◽  
Leg Design

Mobile Minirobot with Hybrid Locomotion

2017 ◽  
Vol 260 ◽  
pp. 51-58 ◽  
Author(s):  
Mihai Olimpiu Tătar ◽  
Claudiu Cirebea
Keyword(s):  
Kinematic Model ◽  
Legged Locomotion ◽  
Electronic Components ◽  
Experimental Prototype ◽  
Locomotion System ◽  
Hybrid Locomotion

In this paper the authors present a mobile minirobot with a hybrid locomotion system. The proposed locomotion system combines the advantages of legged locomotion with the advantages of wheeled locomotion. Due to the proposed structure, the minirobot allows three ways of locomotion: legged, wheeled and combined. The paper describes the experimental prototype, the electronic components needed for controlling the minirobot and it analyses locomotion possibilities by using wheels and legs. The end of the paper presents the kinematic model for a single leg of the minirobot.

Design, Modeling, and Control of a Wheel-Legged Locomotion System for the Environmental Hybrid Robot

2012 ◽  
Author(s):  
Gustavo Freitas ◽  
Fernando Lizarralde ◽  
Liu Hsu ◽  
Vitor Paranhos ◽  
Ney R. Salvi dos Reis ◽  
...  
Keyword(s):  
Legged Locomotion ◽  
Modeling And Control ◽  
Locomotion System ◽  
And Control

Quadrupedal robots trot into the wild

2020 ◽  
Vol 5 (47) ◽  
pp. eabe5218
Author(s):  
Sehoon Ha
Keyword(s):  
Reinforcement Learning ◽  
Natural Environments ◽  
Quadruped Robots

Deep reinforcement learning enables quadruped robots to traverse challenging natural environments using only proprioception.

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