What is the concept of explainable robotics, and how do researchers and practitioners ensure transparency, interpretability, and trustworthiness in robotic systems with complex decision-making algorithms, perception systems, and autonomous behaviors?

Explainable robotics involves providing insights into the internal workings and decision processes of robotic systems to enable users to understand, validate, and trust their behavior. Researchers employ techniques such as model visualization, algorithmic transparency, and user-centered design to enhance explainability and human-robot interaction in safety-critical applications such as autonomous vehicles, healthcare robotics, and collaborative robots in industrial settings.