Mobile Sensing Cluster with Orbiting Mutant for Indistinguishable Events in Noisy Environments.

Applying autonomous mobile systems (AMSs) such as robots and unmanned aerial vehicles (UAVs) to search for and capture events where the number of events and locations is unknown, such as rescue situations and damaged structures, has been investigated. AMSs sense the physical information, such as temperature, smell, and sound, emitted from the unknown events to search for and capture them. However, when this sensed information becomes mixed so that events cannot be individually distinguished, search and capture efforts become difficult. The Mutant Mobile Sensing Cluster has been proposed to search for and capture such events by forming multiple swarms. In this method, swarm splits by that an AMS randomly changes into a mutant AMS which secedes from a swarm to search for and capture multiple indistinguishable unknown events. This method, however, requires more time for searching and capturing in a noisy environment, where physical information fluctuates constantly. In addition, a mutant AMS frequently searches in areas where no events exist, resulting in wasted time and degradation of the search performance. In this paper, we propose a Mobile Sensing Cluster with an orbiting mutant to resolve these issues and demonstrate its effectiveness. Our proposed method improves the AMS’ tolerance for physical information noise emitted from events and changes the movement of mutant AMS to orbiting around the swarm, enabling it to search for and capture indistinguishable unknown events in a noisy environment expeditiously.