On Foveated Gaze Control and Combined Gaze and Locomotion Planning

摘要

This chapter presents a foveated active vision planning concept for robot navigation in order to overcome drawbacks of conventional active vision when trading field of view versus measurement accuracy. This is the first approach of task-related control of foveated active vision in the context of humanoid robots as well as localization and mapping. In a typical robot navigation scenario the benefits of foveated active vision have been demonstrated: an improved localization accuracy combined with an extended visible field compared to conventional active vision. As a generic information maximization principle has been used the gaze control strategy is generalizable to other scenarios depending on the definition of the task-related information measures, thereby, allocating vision sensor resources optimally. The second part of this chapter has presented novel concepts of coordinating gaze direction and locomotion planning. Through this planning procedure, all possible trajectories and viewing angles over a specific time horizon are anticipated. This results in significantly improved performance compared to known approaches, which neglect the limitations of the sensors. It is demonstrated that a very accurate environmental model is autonomously produced even if very inaccurate robot and sensor models are used. Such a scheme is ideal for vision-based humanoid robots. The proposed approaches assume time-invariant scenarios. Path planning and gaze control methods for dynamically changing environments are not yet covered and subject to ongoing research.