Approximate Computing for Robotic path planning -- Experimentation, Case Study and Practical Implications

TL;DR

This paper explores the use of approximate computing in robotic path planning within warehouse environments, highlighting the trade-offs between energy efficiency and safety, and demonstrating how uncontrolled approximation can cause robot collisions.

Contribution

It introduces the concept of controlled approximation in multi-robot systems to prevent collisions while leveraging energy savings from approximate computing.

Findings

Uncontrolled approximation can lead to robot collisions.

Controlled approximation can maintain safety while saving energy.

Path planning safety is affected by approximation levels.

Abstract

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.