Context:
Robotics software architecture-based self-adaptive systems (RSASSs) are robotics systems made robust to runtime uncertainty by adapting their software architectures. The research landscape of RSASS approaches is multidisciplinary and fragmented, with many aspects still unexplored or ineffectively shared among communities involved.

Objective:
We aim at identifying, classifying, and analyzing the state of the art of existing approaches for RSASSs from the following perspectives: (i) the key characteristics of approaches and (ii) the evaluation strategies applied by researchers.

Method:
We apply the systematic mapping research method. We selected
primary studies via automatic, manual, and snowballing-based search and selection procedures. We rigorously defined and applied a classification framework composed of 32 parameters and synthesize the obtained data to produce a comprehensive overview of the state of the art.

Results:
This work contributes (i) a rigorously defined classification framework for studies on RSASSs, (ii) a systematic map of the research efforts on RSASSs, (iii) a discussion of emerging findings and implications for future research, and (iv) a publicly available replication package.

Conclusion:
This study provides a solid evidence-based overview of the state of the art in RSASS approaches. Its results can benefit RSASS researchers at different levels of seniority and involvement in RSASS research.@en

Software is widely used, and society increasingly depends on its reliability. However, software has become so complex and it evolves so quickly that we fail to keep it under control. Therefore, we propose intents: fundamental laws that capture a software systems’ intended behavior (resilient, secure, safe, sustainable, etc.). The realization of this idea requires novel theories, algorithms, tools, and techniques to discover, express, verify, and evolve software intents. Thus, future software systems will be able to verify themselves that they meet their intents. Moreover, they will be able to respond to deviations from intents through selfcorrection. In this article we propose a research agenda, outlining which novel theories, algorithms and tools are required.@en