As development of robots with the ability to self-assess their proficiency for accomplishing
tasks continues to grow, metrics are needed to evaluate the characteristics and performance …

This chapter reviews theoretical frameworks and recent advancements in transparency
research and development. The review covers implementation of transparent human …

Humans are increasingly working with intelligent agents—from robots to complex networked
systems—as collaborators rather than tool users, due to the tremendous advancements in …

Collective robotic systems are biologically inspired and advantageous due to their apparent
global intelligence and emergent behaviors. Many applications can benefit from the …

Behaviours of robot swarms often take inspiration from biological models, such as ant
colonies and bee hives. Yet, understanding how these behaviours are actually perceived by …

Due to tremendous advancements in artificial intelligence (AI) and autonomy-related
technologies in recent decades, machines have become more intelligent and sophisticated; …

The ability to adapt and learn can help robots deployed in dynamic and varied
environments. While in the wild, the data that robots have access to includes input from their …

(2) Measurements from a set of metrics that correlate, predict, or set bounds on a robot's
proficiency, or (3) An explanation of the causal factors that led to a particular assertion about …

Collective robotic systems are biologically-inspired and exhibit behaviors found in spatial
swarms (eg, fish), colonies (eg, ants), or a combination of both (eg, bees). Collective robotic …