Swarms of flying robots are promising in many applications due to rapid terrain coverage. However, there are numerous challenges in realising autonomous operation in unknown indoor environments. A new autonomous flight methodology is presented using relative positioning sensors in reference to nearby static robots. The entirely decentralised approach relies solely on local sensing without requiring absolute positioning, environment maps, powerful computation or long-range communication. The swarm deploys as a robotic network facilitating navigation and goal directed flight. Initial validation tests with quadrotors demonstrated autonomous flight within a confined indoor environment, indicating that they could traverse a large network of static robots across expansive environments.

We present ARGoS, a novel open source multi-robot simulator. The main design focus of ARGoS is the real-time simulation of large heterogeneous swarms of robots. Existing robot simulators obtain scalability by imposing limitations on their extensibility and on the accuracy of the robot models. By contrast, in ARGoS we pursue a deeply modular approach that allows the user both to easily add custom features and to allocate computational resources where needed by the experiment. A unique feature of ARGoS is the possibility to use multiple physics engines of different types and to assign them to different parts of the environment. Robots can migrate from one engine to another transparently. This feature enables entirely novel classes of optimizations to improve scalability and paves the way for a new approach to parallelism in robotics simulation. Results show that ARGoS can simulate about 10,000 simple wheeled robots 40% faster than real-time.

In the growing field of collective robotics, spatial co-ordination between robots is often critical and usually achieved via local relative positioning sensors. We believe that range and bearing sensing, based on infrared technology, has the potential to fulfil the strict requirements of real-world collective robots. These requirements include: small size, light weight, large range, high refresh rate, immunity against tilting and misalignment, immunity against ambient light changes, and good range and bearing accuracy. Currently, there are no range and bearing systems that have been designed to cope with such strict requirements. This paper presents a custom range and bearing system, based on a novel cascaded filtering technology, complemented by hybrid infrared/Radio Frequency (RF) communication, which has been designed specifically to meet all these expectations. The system has been characterised and tested, proving its viability.