Towards goal-directed biped locomotion: Combining CPGs and motion primitives

Matos, Vitor; Santos, Cristina P.

doi:10.1016/j.robot.2014.08.010

Cited by 18 publications

(8 citation statements)

References 65 publications

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“…In particular, the implemented walking generator is based on the ZMP method and on the work for a NAO robot [2,10]. The second method is the bioinspired Central Pattern generator (CPG) method developed by Matos [1]. A detailed explanation of these controllers can be found in [1,10].…”

Section: A Locomotion Generationmentioning

confidence: 99%

“…The second method is the bioinspired Central Pattern generator (CPG) method developed by Matos [1]. A detailed explanation of these controllers can be found in [1,10]. The used controllers try to simplify the human gait ( Figure 2) into four phases during the gait cycle (0-100%): right leg double support (0-40% stance), right leg single support (40-50% stance), left leg double support (50-62% stance) and left leg single support (62-100% swing) [20].…”

Section: A Locomotion Generationmentioning

confidence: 99%

“…Significant work has already been done to achieve successful solutions for biped walking, using different solutions like Zero Moment Point (ZMP) [2,10], Central Pattern Generators (CPG) [1,12] or reflex-based solutions [3]. However, despite intensive research there remain some unanswered issues related to a more intuitive and easy control of the achieved locomotion.…”

Section: Introductionmentioning

confidence: 99%

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Looking for motor synergies in Darwin-OP biped robot

Cunha

Vieira

Costa

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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In humans, the system that controls several biomechanical tasks has a modular organization (muscle synergies). While the muscle synergies in human walking were already studied deeply, this phenomenon in robotic system is not so explored and could bring simpler controllers requiring a minor number of parameters. So, the purpose of this work is to acquire and interpret synergies from selected joint signals in order to answer some specific research questions regarding the verification of synergistic control of a biped robot in a walking activity, e.g, the number of synergies, their activation profiles, their mechanical role, their quality to reproduce/control walking motions, etc. The selected robotic system was the Darwin-OP robot when walking both with a model based and a bio-inspired controller. Tests were performed with the simulated and real robot.The results appear to suggest that the extraction of synergies are quite useful for the robotic locomotion, since with only 2 synergies, is possible to reconstruct the signals of the studied joints. The biomechanical role for each determined synergy is described based on the functional transformation between sensorimotor signals and biomechanical output. Besides, the robustness of the determined synergies is verified in the locomotor activation pattern across strides and across speeds when the mechanical requirements do not change to a large extent.

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Section: A Locomotion Generationmentioning

confidence: 99%

Section: A Locomotion Generationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Looking for motor synergies in Darwin-OP biped robot

Cunha

Vieira

Costa

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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“…For reaching to any desirable locomotion scenario, in our previous works such as [22,23], adaptable CPG networks are developed, which encode foothold positions in respect to the planar obstacles as a forbidden area which can be modulated CPG by feedback signals. Alternatively, references like [24] applied different adaption rules with adaptive oscillators, which called adaptable ring rules. They used their algorithm for reaching to gait switching, while the duty factor and speed would be changed continuously.…”

Section: Introductionmentioning

confidence: 99%

Bio-inspired central pattern generator for development of Cartesian motor skills for a Quadruped Robot

Asadi¹,

Khorram²,

Moosavian³

2021

World J. Adv. Res. Rev.

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Central Pattern Generator (CPG) plays a significant role in the generation of diverse and stable gaits patterns for animals as well as controlling their locomotion. The main contributions of this paper are the ability to develop the Cartesian motor skills and coordinating legs of the quadruped robot for gait adaption and its nominal characteristics with CPG approach. Primary, a predefined relationship between an excitation signal and essential parameters of the CPG design is programmed. Next, the coordinated oscillator's rhythmic patterns by CPG and accordingly output gait diagrams for each foot of the robot are attained. Then, these desirable features such as predictive modulation and programming the gait event sequences including leg-lifting sequences and step length, duration of the time of each footstep within a gait, coordination of swing and stance phases of all legs are calculated in terms of different spatio_temporal vectors. Furthermore, a novel Cartesian footstep basis function is designed based on the robot characteristics and consequently, the associated spatio-temporal vectors can be inserted to it, which caused to spanning the space of possible gait timing in Cartesian space. Next, Cartesian footstep planner can be computed the swing foot trajectories in workspace along movement axes and then according to these footholds and feet placement, ZMP (Zero Moment Point) reference trajectory will be calculated and obtained. Therefore, COG (Center of Gravity) trajectory can be computed by designing a preview controller on the basis of the desired ZMP trajectory. Finally, to demonstrate the effectiveness of the proposed algorithm, it is implemented on a quadruped robot on both simulation or experimental implementations and the results are compared and discussed with other references.

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“…The advantage of the phase oscillators is that they can always produce stable phase entrainments because they only contain the phase transition information of the robotic locomotion. 35 Now, most CPG controllers have been developed to regulate the locomotion of terrestrial bionic robots. Few studies have been conducted to apply the CPG technique in the locomotion control of amphibious robots.…”

Section: Introductionmentioning

confidence: 99%

Central pattern generator and feedforward neural network-based self-adaptive gait control for a crab-like robot locomoting on complex terrain under two reflex mechanisms

Wang

Chen

Han

2017

International Journal of Advanced Robotic Systems

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Although quite a few central pattern generator controllers have been developed to regulate the locomotion of terrestrial bionic robots, few studies have been conducted on the central pattern generator control technique for amphibious robots crawling on complex terrains. The present article proposes a central pattern generator and feedforward neural networkbased self-adaptive gait control method for a crab-like robot locomoting on complex terrain under two reflex mechanisms. In detail, two nonlinear ordinary differential equations are presented at first to model a Hopf oscillator with limit cycle effects. Having Hopf oscillators as the basic units, a central pattern generator system is proposed for the waveform-gait control of the crab-like robot. A tri-layer feedforward neural network is then constructed to establish the one-to-one mapping between the central pattern generator rhythmic signals and the joint angles. Based on the central pattern generator system and feedforward neural network, two reflex mechanisms are put forward to realize selfadaptive gait control on complex terrains. Finally, experiments with the crab-like robot are performed to verify the waveform-gait generation and transition performances and the self-adaptive locomotion capability on uneven ground.

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Towards goal-directed biped locomotion: Combining CPGs and motion primitives

Cited by 18 publications

References 65 publications

Looking for motor synergies in Darwin-OP biped robot

Looking for motor synergies in Darwin-OP biped robot

Bio-inspired central pattern generator for development of Cartesian motor skills for a Quadruped Robot

Central pattern generator and feedforward neural network-based self-adaptive gait control for a crab-like robot locomoting on complex terrain under two reflex mechanisms

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