This paper presents a framework for the safety-critical control of robotic systems, when safety is defined on safe regions in configuration space. To maintain safety, we synthesize velocity based barrier function theory without relying -- potentially complicated high-fidelity dynamical model robot. Then, track with tracking controller. culminates model-free critical control. We prove theoretica...

cooperative object manipulation control of rigid-flexible multi-body systems in space is studied in this paper. during such tasks, flexible members like solar panels may get vibrated that in turn may lead to some oscillatory disturbing forces on other subsystems, and consequently produces error in the motion of the end-effectors of the cooperative manipulating arms. therefore, to design and dev...

Memory properties of fractional-order operators are considered for an input-output data model highly uncertain nonlinear systems. The arises by relating the variation output to input; instantaneous gain is computed through a fuzzy inference network, whose consequences adapted online on gradient descent rule. nature proposed relaxes stringent conditions data-driven schemes, allowing changes in s...

We develop an approach to improve the learning capabilities of robotic systems by combining learned predictive models with experience-based state-action policy mappings. Predictive provide understanding task and dynamics, while (model-free) mappings encode favorable actions that override planned actions. refer our systematically model-based model-free methods as hybrid learning. Our efficiently...