Push recovery of a quadruped robot on challenging terrains

Khorram, Mahdi; Moosavian, S. Ali A.

doi:10.1017/s0263574716000394

Cited by 19 publications

(14 citation statements)

References 29 publications

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“…robot shows that the balance control method that is based on kinematics and empirical methods can correct the interference. Mahdi Khorram [61,62] proposed a robot balance recovery framework to deal with external unknown interference, as shown in Figure 14. The whole-body dynamics model is used in the framework that enhances the robot's ability to recovery balance with all degrees of freedom.…”

Section: Coping With the Self-disturbance And External Impactmentioning

confidence: 99%

Survey of Quadruped Robots Coping Strategies in Complex Situations

Shao

Sun

et al. 2019

Electronics

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As an important branch of mobile robots, quadruped robots have high flexibility, high adaptability, and high dynamics, which provide excellent maneuverability and environmental adaptability. In the past ten years, researchers have done a lot of research on the ability of the quadruped robot to cope with the complex environment and published many results in order to make the working environment of the quadruped robot closer to reality. This paper collected these research results and divided these literatures into three categories according to different situations: crossing challenging terrain, walking on slope, and coping with interference, respectively, introducing representative methods. The purpose of this review is to summarize and analyze the previous research results and provide guidance for future research on quadruped robots in complex situations.

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Section: Coping With the Self-disturbance And External Impactmentioning

confidence: 99%

Survey of Quadruped Robots Coping Strategies in Complex Situations

Shao

Sun

et al. 2019

Electronics

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“…The mapping of the contact forces to the joint torques is solved considering the multibody dynamics of the system. Khorram and Moosavian [7] proposed a controller for quadruped robots to restore the robot equilibrium in the standing phase when exerting external pushes. The method developed a full-dynamics model, with constraints of the stability, friction and saturation constraints to derive the desired forces/torques which can achieve body balance.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Quadruped Balance Control for Dynamic Environments Using Maximum-Entropy Reinforcement Learning

Sun

Ling

et al. 2021

Sensors

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External disturbance poses the primary threat to robot balance in dynamic environments. This paper provides a learning-based control architecture for quadrupedal self-balancing, which is adaptable to multiple unpredictable scenes of external continuous disturbance. Different from conventional methods which construct analytical models which explicitly reason the balancing process, our work utilized reinforcement learning and artificial neural network to avoid incomprehensible mathematical modeling. The control policy is composed of a neural network and a Tanh Gaussian policy, which implicitly establishes the fuzzy mapping from proprioceptive signals to action commands. During the training process, the maximum-entropy method (soft actor-critic algorithm) is employed to endow the policy with powerful exploration and generalization ability. The trained policy is validated in both simulations and realistic experiments with a customized quadruped robot. The results demonstrate that the policy can be easily transferred to the real world without elaborate configurations. Moreover, although this policy is trained in merely one specific vibration condition, it demonstrates robustness under conditions that were never encountered during training.

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“…The design of control system for a multi-legged robot is a challenging issue due to its high nonlinear dynamics, significant couplings between their degrees of freedoms, unknown model parameters, and environment constraints (Farid et al, 2018b; Gor et al, 2015). In this context, the push recovery of a quadruped robot on challenging terrains is addressed in Khorram and Moosavian (2017), where a full-dynamics-based controller is proposed to restore the balanced configuration, despite exerting external pushes. Kazemi et al (2013) formulated the dynamics of a five-link planar under-actuated mechanical model of the quadruped robot with four actuated joints and then studied an exponential stabilization of a quadruped robot based on the back-stepping approach.…”

Section: Introductionmentioning

confidence: 99%

Dynamic-free robust adaptive intelligent fault-tolerant controller design with prescribed performance for stable motion of quadruped robots

2019

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In this article, a robust adaptive intelligent fault-tolerant controller with prescribed performance is proposed for an uncertain quadruped robot with actuator fault. The control system comprised of three terms: (1) a full-state feedback controller which includes the prescribed performance function, (2) an adaptive intelligent wavelet-based Takagi-Sugeno fuzzy network (TSFN), and (3) a robust control term. The proposed controller does not utilize the robot dynamic model. A wavelet-based TSFN is utilized to approximate adaptively the lumped nonlinear terms, parameter uncertainties, and defective torque signal. The wavelet block acts as a feature extractor, reduces the number of fuzzy rules, and also acts as a normalization function. The parameters of TSFN are tuned online by an adaptive law based on Lyapunov stability theory. The proposed controller guarantees the desired specification such as minimum speed of convergence, maximum steady-state error, overshoot concerning the position tracking error, and also bounded closed-loop signals. Numerical simulations on MATLAB/SimMechanics environment demonstrate the stable walking of the quadruped robot in the presence of the actuator faults and parameter uncertainties.

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Push recovery of a quadruped robot on challenging terrains

Cited by 19 publications

References 29 publications

Survey of Quadruped Robots Coping Strategies in Complex Situations

Survey of Quadruped Robots Coping Strategies in Complex Situations

Adaptive Quadruped Balance Control for Dynamic Environments Using Maximum-Entropy Reinforcement Learning

Dynamic-free robust adaptive intelligent fault-tolerant controller design with prescribed performance for stable motion of quadruped robots

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