Learning effects in variable autonomy human-robot systems: How much training is enough?
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Colleges, School and Institutes
- Extreme Robotics Lab (ERL) and National Center for Nuclear Robotics (NCNR)
This paper investigates learning effects and human operator training practices in variable autonomy robotic systems. These factors are known to affect performance of a human-robot system and are frequently overlooked. We present the results from an experiment inspired by a search and rescue scenario in which operators remotely controlled a mobile robot with either Human-Initiative (HI) or Mixed-Initiative (MI) control. Evidence suggests learning in terms of primary navigation task and secondary (distractor) task performance. Further evidence is provided that MI and HI performance in a pure navigation task is equal. Lastly, guidelines are proposed for experimental design and operator training practices.
|Title of host publication||2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019|
|Publication status||Published - Oct 2019|
|Event||2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 - Bari, Italy|
Duration: 6 Oct 2019 → 9 Oct 2019
|Name||Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics|
|Conference||2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019|
|Period||6/10/19 → 9/10/19|