Multimodal sensor based control for human robot interaction
The methods required to make humans and robots interact and collaborate are the subject of research in physical human robot interaction (pHRI) One of the main issues, particularly when physical contact can occur between the two, is safety. A second fundamental requirement to establish pHRI is intuitive control by the human operator, in particular when s/he is non expert. Sensor based control can address both issues, by closing the perception to action loop, in a way that may well be assimilated to that of the lower motor neurons in our nervous system. Traditionally, heterogeneous sensor data was fed to fusion algorithms (e.g. Kalman or Bayesian based) so as to provide state estimation for modeling the environment. However, since robot sensors generally measure different physical phenomena, it is preferable to use them directly in the low level servo controller rather than to apply them to multi sensory fusion or to design complex state machines. This idea, originally proposed in the hybrid position force control paradigm, when extended to multiple sensors brings new challenges to the control design; challenges related to the task representation and to the sensor characteristics (synchronization, hybrid control, task compatibility, etc. The rationale behind my work has precisely been to use sensor based control as a means to facilitate the physical interaction between robots and humans. In particular, I have utilized vision, proprioceptive force, touch and distance to address pHRI case studies, targeting different applications and robot platforms. My research has followed four main axes: teach and repeat navigation of wheeled mobile robots, collaborative industrial manipulation with safe physical interaction, force and visual control for interacting with humanoid robots, and shared robot control. Each of these axes will be presented here, before concluding with a general view of the issues at stake, and on the research projects that I plan to carry out in the upcoming years.