PICO is an interactive tabletop surface that can track the positions of especially tagged pucks on top of it. These are wave electro magnets. It can also move these pucks under self or control. We developed PICO to explore the idea of mechanical constraints as a new way to interact with computers during a problem solving tasks.
In this simple example, the computer is trying to form an equilateral triangle with a three pucks. When the user moves one of them, the computer responds by pulling all of the pucks towards restoring the equilateral triangle.
PICO uses the physics of the interaction between the objects on the tabletop, as a means to combine the behavior to finance offer with the user’s actions.
User can constrain the motion of any of the paths with his or her hands or any other physical object. In this cellular telephone tag, placement application, the goal is to maximize the overall network coverage by moving and reconfiguring the towers.
User can associate each path with the cellular telephone tower. And, place it on a desired location on the map. Even as this appends and zoom the map, the motions of the pucks remain consistent with the softer representation of each tower’s current position.
The computer autonomously tries to move the towers to optimize their location, using the assimilated and yelling process, while the user can guide the optimization process using mechanical constraints like this flexible barrier.
Let us take a look at some more examples on mechanical constraints. One can lock an object in place just by holding it, or by placing away on top of it, making it too heavy for the computer to move. This roll of tape allows the puck to move freely within a limited area.
These colors ensure a certain minimum distance between pucks. As mechanical constraints are added and taken away, the computer continues trying to optimize the overall lamp as the cellular telephone towers. These barrier confines the puck to a user-defined region at a table.
A ring ensures that these two pucks stay within a certain maximum distance of each other and the optimization continues within this constraint. These constraints can be combined as desired. If one places a lighter weight on top of a puck, the puck will be more reluctant to move that other pucks. Making it associated to tower position more difficult to change in cell form.
The upset effects can be obtained using a slippery material like Teflon. Here, we use some soap and water as lubricant to make towers on a specific part of the map easier to move. The variety of physical objects that can be used as mechanical constraints in PICO, is quiet large. In the context of an application like cellular telephone tower layout, these mechanical constraints served to balance the computer’s boot force quantitative optimization with the users intuitive understanding of subtle issues that maybe difficult to quantify.
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