Understanding the Stability of Deep Control Policies for Biped ...

Title:Understanding the Stability of Deep Control Policies for Biped Locomotion ... Abstract:Achieving stability and robustness is the primary ...

Understanding the stability of deep control policies for biped ...

An episode of simulation is considered successful if the biped withstands a push and remains walking for 10 s while maintaining its balance. If ...

In this paper, we evaluate the push-recovery stability of deep policies under various conditions (e.g., walking speed, stride length, the level ...

Understanding the stability of deep control policies for biped ...

Understanding the stability of deep control policies for biped locomotion ... Although deep control policies are more advantageous compared with previous ...

Understanding the Stability of Deep Control Policies for Biped ...

Achieving stability and robustness is the primary goal of biped locomotion control. Recently, deep reinforce learning (DRL) has attracted ...

Understanding the stability of deep control policies for biped ... - OUCI

Understanding the stability of deep control policies for biped locomotion ... biped walking control. ACM Trans. Gr. 29(4), 1–9 (2010). (Article No. 130)

Understanding the stability of deep control policies for biped ...

A dynamic biped locomotion robot which realizes high speed movement is presented. Its walking cycle is about 0.45 s, its speed is about 0.8m/s, ...

Papers with Code - Hwangpil Park

Understanding the Stability of Deep Control Policies for Biped Locomotion ... The goal of this study is to answer these questions by evaluating the push-recovery ...

Push-recovery stability of biped locomotion - ACM Digital Library

Understanding the correlation between gait and stability is an important aspect of biped controller design. We studied this issue in two sets of experiments ...

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Understanding the Stability of Deep Control Policies for Biped Locomotion. Download. Open Access. ArXiv. Profile Image. Hwangpil Park · Profile Image. Ri Yu.

[PDF] Mesh-based Tools to Analyze Deep Reinforcement Learning ...

A mesh-based approach to analyze stability and robustness of the policies obtained via deep reinforcement learning for various biped gaits of a five-link ...

Implementation of Deep Deterministic Policy Gradients for ...

The DDPG network determines the desired step length and duration, and a separate controller, the stance controller, controls the biped during the stance phase.

Robust biped locomotion using deep reinforcement learning on top ...

Several research groups have been exploring how to learn from previous experiences to improve stability and robustness. We believe the fourth type is the best ...

Stability Control of a Biped Robot on a Dynamic Platform Based on ...

By adding the inverse kinematics techniques, the dimension of action space was significantly reduced. ... Finally, a model-free optimizer based on DQN (λ) was ...

Mesh-based Tools to Analyze Deep Reinforcement Learning ...

Mesh-based Tools to Analyze Deep Reinforcement Learning Policies for Underactuated Biped Locomotion ... Control of biped robots involves many challenges: their ...

Stability Control of a Biped Robot on a Dynamic Platform Based on ...

Simulation results showed that the proposed hybrid reinforcement learning mechanism enabled the NAO robot to balance on an oscillating platform with ...

Using deep reinforcement learning to learn high-level policies on ...

However, domain randomization can make the problem of finding stable controllers even more challenging, especially for under actuated bipedal robots. In this ...

Real-time deep learning-based model predictive control of a 3-DOF ...

Our research utilized deep learning to enhance the control of a 3 Degrees of Freedom biped robot leg. We created a dynamic model based on a ...

Learning Push Recovery Behaviors for Humanoid Walking Using ...

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[Retracted] Application of Neural Network in the Stability of Biped ...

This article aims to study the application of neural networks in the stability of biped robots and the embedded control of walking mode.