CPG-based gait planning of a quadruped robot for crossing obstacles

Asadi, Fatemeh; Khorram, Mahdi; Moosavian, S. Ali A.

doi:10.1109/icrom.2015.7367787

Cited by 7 publications

(10 citation statements)

References 15 publications

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“…It controls and adjusts the periodic stepping sequence, and also the diffusive coupling is used in the CPG. These coupling equations are presented in the below equations [22,23].…”

Section: Design Of Central Pattern Generator With Coupled Nonlinear Oscillatorsmentioning

confidence: 99%

“…After discretization process of the ZMP equations in (23), a ZMP tracking servo controller is designed for compensation of ZMP tracking error and additional constraints associated from terminal ZMP and initial and final conditions [22][23]. Based on the reference ZMP trajectory, 𝑝 𝑟𝑒𝑓 (i), the control problem can be determined as:…”

Section: Deriving Cog Path Generation From Cartesian Footstep Plannermentioning

confidence: 99%

“…Also, since the final conditions are only defined, these equations must be resolved backwards. When the𝑄 𝑒 , 𝑄 𝑥 , R matrices are obtained, the optimal input, 𝑈 𝑐𝑜𝑛 , can be computed by equation ( 25) and the COG path can be computed by equation (23). In summary, the COG path generation algorithm is plotted in (figure 7).…”

Section: Subject To Zmp Equations (Equations 23)mentioning

confidence: 99%

“…However, with applying their approach, the ability to define any desirable scenario for gait event sequences is not possible and only the limited set of gaits can be reachable. 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.…”

Section: Introductionmentioning

confidence: 99%

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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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“…It controls and adjusts the periodic stepping sequence, and also the diffusive coupling is used in the CPG. These coupling equations are presented in the below equations [22,23].…”

Section: Design Of Central Pattern Generator With Coupled Nonlinear Oscillatorsmentioning

confidence: 99%

Section: Deriving Cog Path Generation From Cartesian Footstep Plannermentioning

confidence: 99%

Section: Subject To Zmp Equations (Equations 23)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Asadi¹,

Khorram²,

Moosavian³

2021

World J. Adv. Res. Rev.

View full text Add to dashboard Cite

show abstract

“…As said before, estimation of uncertainty with dynamical states is important in filtering problems and Bayesian approach is a strong method for approximation of posterior status of these disturbances. Some references like [10] and [11] is used multiple model methods and state augmentation approach which is developed from Bayesian formulations. On the other hand, references like [12,13 and 14] is used and developed Bayesian approach based on approximation of posterior distribution and one of the important advantages of this algorithm is related to low computational cost time.…”

Section: Introductionmentioning

confidence: 99%

Bayesian approximation for parameterized KALMAN filter for investigation and simulation of unknown noise variance trajectory following in state space models with different noise distributions

Farhad Asadi,

S. Hossein Sadati

2024

Open Access Res. J. Sci. Technol.

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Bayesian approach can be used for parameter identification and extraction in state space models and its ability for analyzing sequence of data in dynamical system is proved in different literatures. In this paper, Bayesian approach for approximation of variances in measurement noise with KALMAN filter is applied for estimation of the dynamical state and measurement data in discrete dynamical system. Detection of uncertainty and estimation of those can be done simultaneously with adaptive KALMAN filter. This algorithm at each step time estimates noise variance and state of system with KALMAN filter. Then, approximation is formed at each step separately and at each step sufficient statistics of the state and noise variances are computed with a fixed-point iteration of a KALMAN filter. For showing influence of variance in measurement data on algorithm different simulations is applied. First, effect of variance and its distribution on detection performance is simulated in KALMAN filter without Bayesian formulation. Then simulation is applied to KALMAN filter with ability of variance tracking of measurement data.in these simulations, influence of distribution of measurement data in each step is estimated and true variance of data is obtained by algorithm and is compared in different scenarios. Afterwards, one typical modeling of nonlinear state space model with inducing noise measurement is simulated by this approach. Finally, the performance and the important limitations of this algorithm in these simulations are explained.

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A Review of Quadruped Robots: Structure, Control, and Autonomous Motion

Fan,

Pei,

Wang

et al. 2024

Advanced Intelligent Systems

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With their unique point‐contact ability with the ground and exceptional adaptability to complex terrains, quadruped robots have become a focal point in the fields of automation and robotic engineering. Significant research progress has been made in aspects such as structural design, motion planning, and balance control of these robots. However, a primary challenge in current research lies in further enhancing the dynamic performance, environmental adaptability, and payload capacity. In this article, research achievements in key technical areas of quadruped robots, encompassing structural design, gait planning, traditional control strategies, intelligent control strategies, and autonomous movement, are comprehensively discussed. The focus of the article is on analyzing trends in intelligence and technological innovation within the aforementioned areas, aiming to provide robust theoretical support and forward‐looking technical guidance for quadruped robots research. Additionally, it offers valuable references for scholars engaged in this field.

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CPG-based gait planning of a quadruped robot for crossing obstacles

Cited by 7 publications

References 15 publications

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

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

Bayesian approximation for parameterized KALMAN filter for investigation and simulation of unknown noise variance trajectory following in state space models with different noise distributions

A Review of Quadruped Robots: Structure, Control, and Autonomous Motion

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