Abstract

Environmental sciences rely heavily on accurate, timely and complete data sets which are often collected manually at significant risks and costs. Robotics and mobile sensor networks can collect data more effectively and with higher spatial-temporal resolution compared to manual methods while benefiting from expanded operational envelopes and added data collection capabilities. In future, robotics and AI will be an indispensable tool for data collection in complex environments, enabling the digitalisation of forests, lakes, off-shore energy systems, cities and the polar environment. However, such future robot solutions will need to operate more flexibly, robustly and efficiently than they do today.

This talk will present how animal-inspired robot design methods can integrate adaptive morphologies, functional materials and energy-efficient locomotion principles to enable this new class of environmental robotics. The talk will also include application examples, such as flying robots that can place sensors in forests, aerial-aquatic drones for autonomous water sampling, drones for aerial construction and repair, and impact-resilient drones for safe operations in underground and tunnel systems.