[go: up one dir, main page]

Liu et al., 2020 - Google Patents

Workspace trajectory generation method for humanoid adaptive walking with dynamic motion primitives

Liu et al., 2020

View PDF
Document ID
10951086475629972321
Author
Liu C
Geng W
Liu M
Chen Q
Publication year
Publication venue
IEEE Access

External Links

Snippet

To properly function in real-world environments, a humanoid robot must be able to adapt its walking gait to new situations. In this paper, an adaptive bipedal walking control method that uses sensory feedback to modulate dynamic movement primitive (DMP) parameters is …
Continue reading at ieeexplore.ieee.org (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/04—Architectures, e.g. interconnection topology

Similar Documents

Publication Publication Date Title
Gangapurwala et al. Rloc: Terrain-aware legged locomotion using reinforcement learning and optimal control
Xiong et al. 3-d underactuated bipedal walking via h-lip based gait synthesis and stepping stabilization
Kim et al. Not only rewards but also constraints: Applications on legged robot locomotion
Nakanishi et al. Learning from demonstration and adaptation of biped locomotion
Yang et al. Cajun: Continuous adaptive jumping using a learned centroidal controller
Tan et al. A hierarchical framework for quadruped locomotion based on reinforcement learning
Reher et al. Inverse dynamics control of compliant hybrid zero dynamic walking
CN114740875B (en) Robot rhythmic motion control method and system based on neural oscillator
Oliveira et al. Multi-objective parameter CPG optimization for gait generation of a biped robot
Liu et al. Adaptive walking control of biped robots using online trajectory generation method based on neural oscillators
Liu et al. Workspace trajectory generation method for humanoid adaptive walking with dynamic motion primitives
Gasparri et al. Efficient walking gait generation via principal component representation of optimal trajectories: application to a planar biped robot with elastic joints
CN117572877B (en) Biped robot gait control method, biped robot gait control device, storage medium and equipment
Li et al. Learning agile bipedal motions on a quadrupedal robot
Liu et al. Rhythmic-reflex hybrid adaptive walking control of biped robot
Schumacher et al. Natural and robust walking using reinforcement learning without demonstrations in high-dimensional musculoskeletal models
Lee et al. Integrating model-based footstep planning with model-free reinforcement learning for dynamic legged locomotion
WO2023161228A1 (en) Methods for training a neural network and for using said neural network to stabilize a bipedal robot
Tan et al. A hierarchical framework for quadruped omnidirectional locomotion based on reinforcement learning
Zhang et al. Achieving stable high-speed locomotion for humanoid robots with deep reinforcement learning
WO2021095471A1 (en) Biped walking robot and method of controlling biped walking robot
Wei et al. Motion Control of High-Dimensional Musculoskeletal Systems with Hierarchical Model-Based Planning
Tan et al. Perceptive locomotion with controllable pace and natural gait transitions over uneven terrains
Koolen et al. Capturability-based analysis and control of legged locomotion
Chen et al. Pretraining-finetuning Framework for Efficient Co-design: A Case Study on Quadruped Robot Parkour