1,283 research outputs found
Dynamic modeling, property investigation, and adaptive controller design of serial robotic manipulators modeled with structural compliance
Research results on general serial robotic manipulators modeled with structural compliances are presented. Two compliant manipulator modeling approaches, distributed and lumped parameter models, are used in this study. System dynamic equations for both compliant models are derived by using the first and second order influence coefficients. Also, the properties of compliant manipulator system dynamics are investigated. One of the properties, which is defined as inaccessibility of vibratory modes, is shown to display a distinct character associated with compliant manipulators. This property indicates the impact of robot geometry on the control of structural oscillations. Example studies are provided to illustrate the physical interpretation of inaccessibility of vibratory modes. Two types of controllers are designed for compliant manipulators modeled by either lumped or distributed parameter techniques. In order to maintain the generality of the results, neither linearization is introduced. Example simulations are given to demonstrate the controller performance. The second type controller is also built for general serial robot arms and is adaptive in nature which can estimate uncertain payload parameters on-line and simultaneously maintain trajectory tracking properties. The relation between manipulator motion tracking capability and convergence of parameter estimation properties is discussed through example case studies. The effect of control input update delays on adaptive controller performance is also studied
Nonlinear dynamics of a conical dielectric elastomer oscillator with switchable mono to bi‐stability
A Robust Open-source Tendon-driven Robot Arm for Learning Control of Dynamic Motions
A long-lasting goal of robotics research is to operate robots safely, while
achieving high performance which often involves fast motions. Traditional
motor-driven systems frequently struggle to balance these competing demands.
Addressing this trade-off is crucial for advancing fields such as manufacturing
and healthcare, where seamless collaboration between robots and humans is
essential. We introduce a four degree-of-freedom (DoF) tendon-driven robot arm,
powered by pneumatic artificial muscles (PAMs), to tackle this challenge. Our
new design features low friction, passive compliance, and inherent impact
resilience, enabling rapid, precise, high-force, and safe interactions during
dynamic tasks. In addition to fostering safer human-robot collaboration, the
inherent safety properties are particularly beneficial for reinforcement
learning, where the robot's ability to explore dynamic motions without causing
self-damage is crucial. We validate our robotic arm through various
experiments, including long-term dynamic motions, impact resilience tests, and
assessments of its ease of control. On a challenging dynamic table tennis task,
we further demonstrate our robot's capabilities in rapid and precise movements.
By showcasing our new design's potential, we aim to inspire further research on
robotic systems that balance high performance and safety in diverse tasks. Our
open-source hardware design, software, and a large dataset of diverse robot
motions can be found at https://webdav.tuebingen.mpg.de/pamy2/
- …