Swarm construction: ant-inspired processes for teams of building robots. Construction and manufacturing can be dangerous, wasteful industries—prime candidates for automation by teams of mobile robot builders. However, our understanding of how to program robots for teamwork is limited. This project aims to understand how colonies of weaver ants build complex nest structures, using novel 3D-imaging and ant tracking techniques. The anticipated outcomes of the project are i) a framework for how indi ....Swarm construction: ant-inspired processes for teams of building robots. Construction and manufacturing can be dangerous, wasteful industries—prime candidates for automation by teams of mobile robot builders. However, our understanding of how to program robots for teamwork is limited. This project aims to understand how colonies of weaver ants build complex nest structures, using novel 3D-imaging and ant tracking techniques. The anticipated outcomes of the project are i) a framework for how individual-level behaviour drives structure-level outcomes, applicable to many complex systems, and ii) novel software and hardware for robot swarms that can 3D-print structures using ant inspired teamwork strategies. Benefits of the project include new construction technologies that are safer, greener, cheaper and faster.Read moreRead less
Action selection in insects: how a microbrain knows what to do. Identifying what to do demands integrating sensory information with our current physiological state and memory of past experience to select the best possible action. This is the action selection problem. Our project aims to discover how tiny insect brains solve this fundamental problem. The project combines neural recordings from animals exploring virtual reality, behavioural analyses and computational modelling. The expected outco ....Action selection in insects: how a microbrain knows what to do. Identifying what to do demands integrating sensory information with our current physiological state and memory of past experience to select the best possible action. This is the action selection problem. Our project aims to discover how tiny insect brains solve this fundamental problem. The project combines neural recordings from animals exploring virtual reality, behavioural analyses and computational modelling. The expected outcome is a new understanding of the brain as an effective behavioural control system. This will benefit systems and comparative neuroscience. Our findings may also inspire solutions for robotic systems that must operate autonomously in remote and challenging environments such as disaster relief or exploration.Read moreRead less