Detecting Errors in a Humanoid Robot

Abstract

This is an experience report on applying program analysis tools and program monitors to a real-world humanoid robot in simulated and real environments. Humanoid robots, and cyber-physical systems in general, present unique challenges to testing and validation: they have realtime constraints, their runs are typically irreproducible, their tasks are high-level and preclude formal specification, and their software tends to be large and complex. In practice, bugs do cause robots to fail, and methods for analyzing such software has been wanting. This paper presents a case study, in which we find that traditional software bugs like memory errors do cause failures of robots in practice. Dynamic error detectors can be successfully employed to identify such errors – to an extent defined by realtime constraints. Static analysis tools, in their current form, are comparatively of limited use.