2022
DOI: 10.1007/s12555-021-0099-8
|View full text |Cite
|
Sign up to set email alerts
|

Online Gait Generation Method Based on Neural Network for Humanoid Robot Fast Walking on Uneven Terrain

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
3
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
5

Relationship

0
5

Authors

Journals

citations
Cited by 6 publications
(3 citation statements)
references
References 58 publications
0
3
0
Order By: Relevance
“…As a strong technique, NN with strong capabilities of good non‐linear mapping, parallel information processing and self‐learning, has been developed to address the locomotion control and uncertain non‐linear system identification problems in bipedal robot systems [87]. Besides, the NN can reduce the computational burden of motion generation instead of online optimisation, which can guarantee online response speed [88].…”
Section: Learning Strategy‐based Gait Control Methodsmentioning
confidence: 99%
“…As a strong technique, NN with strong capabilities of good non‐linear mapping, parallel information processing and self‐learning, has been developed to address the locomotion control and uncertain non‐linear system identification problems in bipedal robot systems [87]. Besides, the NN can reduce the computational burden of motion generation instead of online optimisation, which can guarantee online response speed [88].…”
Section: Learning Strategy‐based Gait Control Methodsmentioning
confidence: 99%
“…Bipeds. The majority of the studies on bipedal robots employed slopes [76-78, 80, 89, 93-97, 101, 102, 107], steps [3,4,80,81,88,93,95,[98][99][100]104], and blocks placed randomly and separated from each other [77, 79, 83-87, 91, 93]. Five [77,80,89,93,107] of the reviewed papers proposed a combination of, at least, two of them.…”
Section: Methodological Aspectsmentioning
confidence: 99%
“…Different strategies were applied to determine the motion stability in the control loop such as the ZMP method that determines whether the robot CoP is inside the region of the support leg [76,79,84,88,89,101,102]. Other methods defined the motion stability with the CoM trajectory [85,87,90,92,94,100] or joint angles [83,104,107]. Finally, control stability was also addressed by the capacity of the control system to reduce GRF since high contact forces are associated with bouncing, leading to instabilities [81,86].…”
Section: Scientific Evidencementioning
confidence: 99%