Improving performance of robots using human-inspired approaches: a survey
H Qiao, S Zhong, Z Chen, H Wang - Science China Information Sciences, 2022 - Springer
Realizing high performance of ordinary robots is one of the core problems in robotic
research. Improving the performance of ordinary robots usually relies on the collaborative …
research. Improving the performance of ordinary robots usually relies on the collaborative …
Brain-inspired intelligent robotics: Theoretical analysis and systematic application
Traditional joint-link robots have been widely used in production lines because of their high
precision for single tasks. With the development of the manufacturing and service industries …
precision for single tasks. With the development of the manufacturing and service industries …
Neural manifold modulated continual reinforcement learning for musculoskeletal robots
The continual learning and development are significant for robots to learn multiple tasks
sequentially. The difficulty lies in balancing the efficient learning of new tasks and …
sequentially. The difficulty lies in balancing the efficient learning of new tasks and …
A cerebellum-inspired prediction and correction model for motion control of a musculoskeletal robot
It is an important issue that how to regulate the existing control models of musculoskeletal
robots to improve the ability of motion learning and generalization. In this article, based on …
robots to improve the ability of motion learning and generalization. In this article, based on …
Robust motion learning for musculoskeletal robots based on a recurrent neural network and muscle synergies
Musculoskeletal robots with human-like joints, muscles, and actuation mechanisms are
characterized by exceptional dexterity, compliance, and versatility. However, existing …
characterized by exceptional dexterity, compliance, and versatility. However, existing …
Motion learning and generalization of musculoskeletal robot using gain primitives
S Zhong, W Wu - IEEE Transactions on Automation Science …, 2023 - ieeexplore.ieee.org
Organisms have an innate ability to rapidly produce diverse and flexible movement.
Biological motor systems are composed of highly redundant muscle actuators and have …
Biological motor systems are composed of highly redundant muscle actuators and have …
Motion learning for musculoskeletal robots based on cortex-inspired motor primitives and modulation
X Wang, J Chen, W Wu - IEEE Transactions on Cognitive and …, 2023 - ieeexplore.ieee.org
Musculoskeletal robots have structural advantages of flexibility, robustness, and compliance.
However, the control of such musculoskeletal robots is challenging. In particular, the …
However, the control of such musculoskeletal robots is challenging. In particular, the …
Event-triggered sliding-mode control for a discrete-time muscle-driven musculoskeletal system
Y Fan, Y Wu, J Yuan, J Gao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Bionic muscle-driven musculoskeletal systems can dynamically adjust the stiffness between
active and antagonistic muscles to improve stability. However, they retain many problems …
active and antagonistic muscles to improve stability. However, they retain many problems …
Forward dynamics simulation of a simplified neuromuscular-skeletal-exoskeletal model based on the CMA-ES optimization algorithm: framework and case studies
The modeling and simulation of coupled neuromusculoskeletal-exoskeletal systems play a
crucial role in human biomechanical analysis, as well as in the design and control of …
crucial role in human biomechanical analysis, as well as in the design and control of …
A memory and attention-based reinforcement learning for musculoskeletal robots with prior knowledge of muscle synergies
Purpose Limited by the types of sensors, the state information available for musculoskeletal
robots with highly redundant, nonlinear muscles is often incomplete, which makes the …
robots with highly redundant, nonlinear muscles is often incomplete, which makes the …