VizRob: Effective Visualizations to Debug Robotic Behaviors

Miguel Campusano, Alexandre Bergel

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


Building and debugging robotic programs is known to be difficult. The robotic community has produced numerous tools, APIs and middlewares to help debug and trace the construction and execution of robotic behaviors. However, mostof available debugging tools are text and log-oriented, leading toa tedious and ad-hoc debugging activity. In this paper we fully describe VizRob, a tool to debug robotic behaviors using logs and execution time. VizRob producesinteractive visualizations built from log traces within a state machine model, that is, the visual representation of the behavior. VizRob is founded on deficiencies we empirically found from semi-structured interviews and a revision of tutorial materials. A small case study received an initial feedback of VizRob in a robotic software engineering team. Our case study shows: (i) VizRob helps engineers solve intricate debugging scenarios and (ii) engineers perceive VizRob as filling a relevant gap within the current tools for building robotic behavior.

Original languageEnglish
Title of host publicationProceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019
Publication date26. Mar 2019
ISBN (Electronic)9781538692455
Publication statusPublished - 26. Mar 2019
Externally publishedYes
Event3rd IEEE International Conference on Robotic Computing, IRC 2019 - Naples, Italy
Duration: 25. Feb 201927. Feb 2019


Conference3rd IEEE International Conference on Robotic Computing, IRC 2019


  • nested state machines
  • robotic behaviors
  • visualizations


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