Launched in July 2020, Mars 2020 (officially named Perseverance) will be NASA’s latest rover to explore Earth’s nearest neighboring planet. With a mission to look for signs of ancient life on the red planet, Perseverance improves on the hardware platform originally developed for Curiosity, NASA’s current Mars rover, whose planning software was also developed through a collaboration between NASA Ames Research Center and JPL nearly a decade ago. Just as the hardware for Perseverance has been upgraded, so too has the software. COCPIT, the software that will handle Perseverance rover planning, heavily leverages the infrastructure of our team’s current planning tool, Playbook.
Role: Design Integrator
Contribution: Design Strategy, Systems Integration, Interaction Design, QA Testing
Because COCPIT is a branch of Playbook, our team’s core planning software, many of Playbook’s feature sets serve as platforms for COCPIT to build new capabilities, both from a design and technical perspective. During the early phases of the project, our team was actively involved with brainstorming and designing prototypes of what would eventually become foundational features for the COCPIT tool. Today, the NASA Ames design team serves as design integrators, ensuring that features developed for either tool can be generalized and scaled for use across both.
Because of the massive scale of the $2B+ Mars 2020 mission, testing is a continuous and major part of mission priorities. Tests such as engineering readiness tests (ERT's) and operational readiness tests (ORT's) qualify software tools in functional and operational settings. Among these tests are full-scale simulations, called rover operations activities for science team training (ROASTT). These are real-time simulations of a week’s worth of rover planning operations. These design focused simulations involve teams of hundreds of scientists and engineers from around the world testing mission tools in their current state, with the objective of identifying breakdowns in the software and planning processes. Tests like these help keep the COCPIT development team informed of larger system inefficiencies that are less likely to appear during day-to-day user feedback sessions.