Abstract: Soft robotic systems are known for their flexibility and adaptability, but traditional physics-based models struggle to capture their complex, nonlinear behaviors. This study explores a data-driven approach to modeling the volume–flow–pressure relationship in hydraulic soft actuators, focusing on low-complexity models with high accuracy. We perform regression … [Read more...] about Simplifying Data-Driven Modeling of the Volume–Flow–Pressure Relationship in Hydraulic Soft Robotic Actuators: A Practical and Balanced Solution
Actuators
Simplifying Data-Driven Modeling of the Volume–Flow–Pressure Relationship in Hydraulic Soft Robotic Actuators: A Practical and Balanced Solution
Abstract: Soft robotic systems are known for their flexibility and adaptability, but traditional physics-based models struggle to capture their complex, nonlinear behaviors. This study explores a data-driven approach to modeling the volume–flow–pressure relationship in hydraulic soft actuators, focusing on low-complexity models with high accuracy. We perform regression … [Read more...] about Simplifying Data-Driven Modeling of the Volume–Flow–Pressure Relationship in Hydraulic Soft Robotic Actuators: A Practical and Balanced Solution
Reinforcement Learning for High-Speed Quadrupedal Locomotion With Motor Operating Region Constraints: Mitigating Motor Model Discrepancies through Torque Clipping in Realistic Motor Operating Region
This article presents a method for achieving high-speed running of a quadruped robot by considering the actuator torque–speed operating region in reinforcement learning. The physical properties and constraints of the actuator are included in the training process to reduce state transitions that are infeasible in the real world due to motor torque–speed limitations. The gait … [Read more...] about Reinforcement Learning for High-Speed Quadrupedal Locomotion With Motor Operating Region Constraints: Mitigating Motor Model Discrepancies through Torque Clipping in Realistic Motor Operating Region
GeMuCo: Generalized Multisensory Correlational Model for Body Schema Learning
Humans can autonomously learn the relationship between sensation and motion in their own bodies, estimate and control their own body states, and move while continuously adapting to the current environment. On the other hand, current robots control their bodies by learning the network structure described by humans from their experiences, making certain assumptions on the … [Read more...] about GeMuCo: Generalized Multisensory Correlational Model for Body Schema Learning
Variable Transmission Mechanisms for Robotic Applications: A Review [Survey]
Actuators play a crucial role in robotics, determining the force and speed capabilities necessary for varied tasks, directly affecting the performance of the robotic system. With the growing reliance on robotics in both industrial applications and daily life, innovative actuator research has expanded significantly. Despite advances, traditional actuators encounter limitations … [Read more...] about Variable Transmission Mechanisms for Robotic Applications: A Review [Survey]
