Approximate computing is a computation domain which can be used to trade time and energy with quality and therefore is useful in embedded systems. Energy is the prime resource in battery-driven embedded systems, like robots. Approximate computing can be used as a technique to generate approximate version of the control functionalities of a robot, enabling it to ration energy for computation at the cost of degraded quality. Usually, the programmer of the function specifies the extent of degradation that is safe for the overall safety of the system. However, in a collaborative environment, where several sub-systems co-exist and some of the functionality of each of them have been approximated, the safety of the overall system may be compromised. In this paper, we consider multiple identical robots operate in a warehouse, and the path planning function of the robot is approximated. Although the planned paths are safe for individual robots (i.e. they do not collide with the racks), we show that this leads to a collision among the robots. So, a controlled approximation needs to be carried out in such situations to harness the full power of this new paradigm if it needs to be a mainstream paradigm in future.

翻译：近似计算是一个计算领域,可以用来交换时间和能源质量,因此在嵌入系统中有用。 能源是电池驱动的嵌入系统的主要资源, 如机器人。 近似计算可以作为一种技术, 用来产生机器人控制功能的近似版本, 使机器人能够以降低质量为计算配给能源。 通常, 该功能的程序员会指定降解程度对系统的整体安全是安全的。 但是, 在合作环境中, 多个子系统同时存在, 并且每个子系统的一些功能被近似, 整个系统的安全可能受到损害。 在本文中, 我们认为多个相同机器人在仓库操作, 机器人的道路规划功能被近似。 尽管计划路径对个体机器人来说是安全的( 即它们不会与架子发生碰撞 ), 我们表明这会导致机器人之间的碰撞。 因此, 在这样的情况下, 需要使用受控制的近似值, 来利用这个新模式的全部力量, 如果它将来需要成为主流模式的话 。