  Autonomous racing in robotics combines high-speed dynamics with the necessity
for reliability and real-time decision-making. While such racing pushes
software and hardware to their limits, many existing full-system solutions
necessitate complex, custom hardware and software, and usually focus on
Time-Trials rather than full unrestricted Head-to-Head racing, due to financial
and safety constraints. This limits their reproducibility, making advancements
and replication feasible mostly for well-resourced laboratories with
comprehensive expertise in mechanical, electrical, and robotics fields.
Researchers interested in the autonomy domain but with only partial experience
in one of these fields, need to spend significant time with familiarization and
integration. The ForzaETH Race Stack addresses this gap by providing an
autonomous racing software platform designed for F1TENTH, a 1:10 scaled
Head-to-Head autonomous racing competition, which simplifies replication by
using commercial off-the-shelf hardware. This approach enhances the competitive
aspect of autonomous racing and provides an accessible platform for research
and development in the field. The ForzaETH Race Stack is designed with
modularity and operational ease of use in mind, allowing customization and
adaptability to various environmental conditions, such as track friction and
layout. Capable of handling both Time-Trials and Head-to-Head racing, the stack
has demonstrated its effectiveness, robustness, and adaptability in the field
by winning the official F1TENTH international competition multiple times.
