Rhythmic-Reflex Hybrid Adaptive Walking Control of Biped Robot

Liu, Chengju; Yang, Jing; An, Kang; Chen, Qijun

doi:10.1007/s10846-018-0889-2

Cited by 12 publications

(10 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The method is tested using simulation and experiment. Recently, control techniques have been applied to balance a biped robot while walking in slopes [14], along with the use of central pattern generation [15,16].…”

Section: Classical Approachesmentioning

confidence: 99%

Learning an Efficient Gait Cycle of a Biped Robot Based on Reinforcement Learning and Artificial Neural Networks

Morales¹,

Rufino²

2019

Applied Sciences

View full text Add to dashboard Cite

Programming robots for performing different activities requires calculating sequences of values of their joints by taking into account many factors, such as stability and efficiency, at the same time. Particularly for walking, state of the art techniques to approximate these sequences are based on reinforcement learning (RL). In this work we propose a multi-level system, where the same RL method is used first to learn the configuration of robot joints (poses) that allow it to stand with stability, and then in the second level, we find the sequence of poses that let it reach the furthest distance in the shortest time, while avoiding falling down and keeping a straight path. In order to evaluate this, we focus on measuring the time it takes for the robot to travel a certain distance. To our knowledge, this is the first work focusing both on speed and precision of the trajectory at the same time. We implement our model in a simulated environment using q-learning. We compare with the built-in walking modes of an NAO robot by improving normal-speed and enhancing robustness in fast-speed. The proposed model can be extended to other tasks and is independent of a particular robot model.

show abstract

Section: Classical Approachesmentioning

confidence: 99%

Learning an Efficient Gait Cycle of a Biped Robot Based on Reinforcement Learning and Artificial Neural Networks

Morales¹,

Rufino²

2019

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…7 In the motion control of the robot, the biological CPG motion control characteristics are transformed into a mathematical model, which is more better than the traditional control method as being applied to the motion control of the robot. 8,9 The oscillating unit models in the CPG control network can be divided into two categories: neuron-based models and nonlinear oscillatorbased models. The former mainly includes Matsuoka 10 model, Kimura et al 11 model, Rulkov 12 model, etc., while the latter mainly includes Kuramoto phase oscillator, 13 Van Der Pol relaxation oscillator, Hopf harmonic oscillator, etc.…”

Section: Introductionmentioning

confidence: 99%

“…19 Liu and Zhang 20 and Liu et al 21 realize the movement of a quadruped robot in different gaits by using a CPG control network composed of different oscillators. Liu et al 8 and Santos et al 22 applied CPG control strategy to the motion control of the biped robot.…”

Section: Introductionmentioning

confidence: 99%

“…Wang et al 23 and Ajalloeian et al 24 combined CPG with a Virtual Model Control (VMC) in a compound control method. Liu et al 8 and Kasaei et al 25 proposed a robot control strategy which combines CPG and Zero Moment Position (ZMP). Hasanzadeh and Tootoonchi 26 and Xue et al 16 proposed a hybrid control strategy based on fuzzy control and CPG.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Motion coordination control of planar 5R parallel quadruped robot based on SCPL-CPG

Chen

Zhang

et al. 2022

Advances in Mechanical Engineering

View full text Add to dashboard Cite

The parallel leg of the quadruped robot has good structural stiffness, accurate movement, and strong bearing capacity, but it is complicated to control. To solve this problem, a series connection of parallel legs (SCPL) was proposed, as well as a control strategy combined with the central pattern generator (CPG). With the planar 5R parallel leg as the research object, the SCPL analysis method was used to analyze the leg structure. The topology of CPG network was built with the Hopf oscillator as the unit model, and the CPG was the core to model the robot control system. By continuously adjusting the parameters in the CPG control system and changing the connection weight, and the smooth transition between gaits was realized. The simulation results show that the SCPL analysis method can be effectively used in the analysis of parallel legs, and the control system can realize the smooth transition between gaits, which verifies the feasibility and effectiveness of the proposed control strategy.

show abstract

“…In simplified technological terms, a pure reflex controller can be regarded as a static state feedback controller, while pure CPG control translates to a time-based feedforward strategy. In this form, both control approaches have been longstanding subjects to robotic investigations of limit cycle motions, mainly applied to quadrupedal (Tsujita et al, 2001;Ferreira et al, 2015) and bipedal locomotion (Endo et al, 2004;Liu et al, 2019). However, only more recently have these approaches been applied to biomimetic models that take into account the major constraints of the CNS.…”

Section: Introductionmentioning

confidence: 99%

Adapting Highly-Dynamic Compliant Movements to Changing Environments: A Benchmark Comparison of Reflex- vs. CPG-Based Control Strategies

et al. 2021

View full text Add to dashboard Cite

To control highly-dynamic compliant motions such as running or hopping, vertebrates rely on reflexes and Central Pattern Generators (CPGs) as core strategies. However, decoding how much each strategy contributes to the control and how they are adjusted under different conditions is still a major challenge. To help solve this question, the present paper provides a comprehensive comparison of reflexes, CPGs and a commonly used combination of the two applied to a biomimetic robot. It leverages recent findings indicating that in mammals both control principles act within a low-dimensional control submanifold. This substantially reduces the search space of parameters and enables the quantifiable comparison of the different control strategies. The chosen metrics are motion stability and energy efficiency, both key aspects for the evolution of the central nervous system. We find that neither for stability nor energy efficiency it is favorable to apply the state-of-the-art approach of a continuously feedback-adapted CPG. In both aspects, a pure reflex is more effective, but the pure CPG allows easy signal alteration when needed. Additionally, the hardware experiments clearly show that the shape of a control signal has a strong influence on energy efficiency, while previous research usually only focused on frequency alignment. Both findings suggest that currently used methods to combine the advantages of reflexes and CPGs can be improved. In future research, possible combinations of the control strategies should be reconsidered, specifically including the modulation of the control signal's shape. For this endeavor, the presented setup provides a valuable benchmark framework to enable the quantitative comparison of different bioinspired control principles.

show abstract

Rhythmic-Reflex Hybrid Adaptive Walking Control of Biped Robot

Cited by 12 publications

References 39 publications

Learning an Efficient Gait Cycle of a Biped Robot Based on Reinforcement Learning and Artificial Neural Networks

Learning an Efficient Gait Cycle of a Biped Robot Based on Reinforcement Learning and Artificial Neural Networks

Motion coordination control of planar 5R parallel quadruped robot based on SCPL-CPG

Adapting Highly-Dynamic Compliant Movements to Changing Environments: A Benchmark Comparison of Reflex- vs. CPG-Based Control Strategies

Contact Info

Product

Resources

About