  The need for a systematic approach to risk assessment has increased in recent
years due to the ubiquity of autonomous systems that alter our day-to-day
experiences and their need for safety, e.g., for self-driving vehicles, mobile
service robots, and bipedal robots. These systems are expected to function
safely in unpredictable environments and interact seamlessly with humans, whose
behavior is notably challenging to forecast. We present a survey of risk-aware
methodologies for autonomous systems. We adopt a contemporary risk-aware
approach to mitigate rare and detrimental outcomes by advocating the use of
tail risk measures, a concept borrowed from financial literature. This survey
will introduce these measures and explain their relevance in the context of
robotic systems for planning, control, and verification applications.
