Spatial Human Robot Interaction Marker Platform (SHRIMP)

ClassicMazeThrough my previous post, I highlighted the Augmented Reality’s (AR) potential to function as a novel paradigm in Human-Robot-Interactions (HRI). Marker-less AR seems more plausible for this work, as it can readily mark points in space, without demanding a prior knowledge of the environment. In other words, we can just look at any random environment and mark any point in that environment real time. By placing a virtual marker, we already saw a demonstration on how can we persistently mark space, so that virtual markers remained persistent under changing perspectives of the camera, often like as if they were real.

Now we will continue from that point onwards, and see how can we apply such an AR-based spatial marker platform into HRI. In this article we make a case study in which we assimilate Augmented Reality into robot navigation. Virtual markers are overlaid on the video feed captured by a camera which in turn is mounted on top of the robot. We mark a point in space, just by placing a virtual AR marker, so then the robot automatically navigates to the location we pointed. My hypothesis here is to prove that just by pointing somewhere in space, we could readily perform HRI tasks – especially navigation. But before moving into application specific details let us dive into some background about HRI and marking space.

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Parallel Tracking And Global Mapping

It’s been a while since I last blogged as I kept receiving piles and piles of work. I do realize now, that research is not a leisurely activity although it may seem like, for a person who is looking from outside. Apart from usual activities of experiments & literature surveys, doing tutorials, marking assignments, writing conference papers, and making presentations are enough to crush a PhD student to his limits. Nevertheless all these implications help in testifying one’s potential for research and the love for science. So I thought of putting all that matters aside and write a post for the sake of contributing to the scientific knowledge. In particular I’d like to share some of the work I did in my research while taking a short break off from my studies.

Marker-less Augmented Reality has been my primary source of curiosity from the day I started my PhD journey. With my research I am exploring the ways in which we can apply AR into HRI (Human-Robot Interactions) and further improve the collaborative patterns between the man and the robot. Consequently I came up with a state-of-the-art interface based on a well- known marker-less AR platform named PTAMM (Parallel Tracking and Multiple Mapping). The interface that I brought up has the capability for marking an arbitrary point in space persistently with a virtual object (AR object). What does the term persistence mean? Suppose you have an AR object that can be clearly seen through your camera. Now you change the camera perspective, move the camera to a different location and return to your AR object from a different direction.  At this instance you must still see the AR object persistently anchored at its original location. The idea may look simple but systems with such a functionality are still rare, even at the existence of powerful AR frameworks (i.e. PTAM, PTAMM).  This is what I describe as Persistent Augmented Reality. My AR interface provides the capability to appear an AR object persistent over time and space, no matter in which direction you change the camera. See the video below. But how does it work?  What are the concepts? are the questions that you might wonder at this point.

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Remote Human-Robot Operations with Adjustable Autonomy

CuriosityThis article was based on the work carried out by [1]. In future NASA’s space missions will include more and more interactive robots. The Curiosity rover that has been recently sent to Mars was a good example for that. These kinds of robots require new remote operation mechanisms for effective use. In such a tele-operated context, a human team should constantly supervise the robot and manually perform tasks whenever needed.

An important aspect of such operations is the ability to allocate tasks between humans and robots effectively. This capability was known as Adjustable Autonomy (Adaptive Autonomy) so that the automation can be smart enough to achieve the autonomy required according to changing situations. Human-robot interactions are closely related to adjustable autonomy, and they both go side-by-side. Apparently, human robot operations are highly dependent upon the scenario so that they become specific to a given robot, thus making it hard to generalize them. Given below is a sub-set of such human robot operations. Continue reading “Remote Human-Robot Operations with Adjustable Autonomy”