Egg-Inspired Deployable Environmental Sensors for Autonomous Multi-Agent Path Planning for UAV and UGV Systems

Underground mines are among the most dangerous and unpredictable environments for both people and machines. When visibility drops and gases spread through tight tunnels, quick decisions are necessary for survival. However, GPS denial and signal interference often cause navigation and communication systems to fail. This paper presents the Sensor Egg, a deployable bio-inspired environmental sensing platform designed to assist future autonomous unmanned ground and aerial vehicles in underground emergency operations. Each unit is protected by a carbon fiber reinforced shell that rights itself after being hit and has sensors for temperature, humidity, gas concentration, and particulate matter. The system continuously sends this information over a wireless network to a visualization interface. This makes a real-time map of the local environment that can be applied to underground mine layouts. An A* path-planning algorithm combines data from multiple Sensor Eggs. This algorithm adjusts moving costs based on local hazard readings, helping autonomous systems find safer routes in emergencies. Indoor deployment tests in the Mineral Science and Engineering Complex (MSEC) building showed that the Sensor Egg network can maintain stable communication and support live visualization and path-planning updates over building-scale distances. In those trials, simulated hazard fields defined on the Egg nodes caused the A* planner to reroute around high-cost regions as the cost map changed. The result is a practical environmental sensing solution that combines field-ready hardware, autonomous decision-making, and real-time safety monitoring into a single, deployable system. This adds a new level of intelligence to robotic operations in high-risk and GPS-denied areas.