Taking Recoveries to Task: Recovery-Driven Development for Recipe-based Robot Tasks

Siddhartha Banerjee, Angel Andres Daruna, David Kent, Weiyu Liu, Jonathan C Balloch, Abhinav Jain, Akshay Krishnan, Muhammad Asif Rana, Harish Ravichandar, Binit Shah, Nithin Shrivatsav, Sonia Chernova

Abstract:

Robot task execution when situated in real-world environments is fragile. As such, robot architectures must rely on robust error
recovery, adding non-trivial complexity to highly-complex robot systems.
To handle this complexity in development, we introduce Recovery-Driven
Development (RDD), an iterative task scripting process that facilitates
rapid task and recovery development by leveraging hierarchical specification, separation of nominal task and recovery development, and situated
testing. We validate our approach with our challenge-winning mobile
manipulator software architecture developed using RDD for the FetchIt!
Challenge at the IEEE 2019 International Conference on Robotics and
Automation. We attribute the success of our system to the level of robustness achieved using RDD, and conclude with lessons learned for developing such systems.