SauRON: Smart Surveillance using Robotic Swarms with Optimized Networks

Smart surveillance is crucial for enhancing situational awareness and ensuring timely responses in dynamic environments. However, a significant challenge is the strategic placement of various surveillance entities within the dynamic environments to ensure full coverage. In this paper, we propose an innovative framework SauRON for efficient area mapping using a swarm of autonomous robots for such strategic placement of those robots working as surveillance entity. SauRON has three modules that operate in an interconnected manner: (i) robots independently navigate in random directions, gathering preliminary data and covering portions of the target area; (ii) the robots establish a communication network and select a leader which provides minimum aggregated latency, dynamically optimizing connections to ensure robust swarm connectivity and efficient data transmission; and (iii) by leveraging initial exploration data, the leader instructs the other robots to reposition to cover the overall area. SauRON’s sensing data compression approach effectively overcomes the challenge of data management in heterogeneous environments, offering significant potential for applications in search and rescue, environmental monitoring, and other scenarios demanding precise area mapping by robotic swarms. Through extensive simulation, we show SauRON provides 38% improvement in blind spot coverage in highly dynamic scenarios.

Recommended citation: Singh, Gaurav and Amatare, Sunday and Roy, Debashri, SauRON: Smart Surveillance using Robotic Swarms with Optimized Networks (January 01, 2025). Available at SSRN: https://ssrn.com/abstract=5143487 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5143487