Swarming refers to the collective motion of a large number of entities. In constrained environments or congested areas, enabling swarming capabilities of the plurality of robots operating in an operating space plays a key role. Infinium Robotics has developed own swarming algorithms for collision-free navigation of UAS, both indoors and outdoors.
Current capability demonstrations include the safe and autonomous navigation of 10 or more agents in a constrained space of less than 150 cubic meters. Current research is aiming to alleviate the computational burden typically associated with similar algorithms as well as to enable different optimization scenarios.
Indoor Positioning for Robots
Six-degrees-of-freedom (6 DOF) estimation plays a key role in aerial robots navigation and control. Different sensor data is usually fused together in outdoors environments (e.g. GPS and INS); however, indoors or in GPS-denied environments, such an approach is unfeasible.
Infinium Robotics is developing an inexpensive alternative solution based on computer vision. The in-house developed algorithms indicate that accuracies better than 5 centimeters in the position estimation (i.e. x, y and z coordinates) and 2 degrees in the attitude estimation (i.e. roll, pitch and yaw angles) are feasible at update frequencies of 30 Hz with relatively low latency. Current research is focused to improve the robustness of such algorithms.
Adaptive and fault tolerant controllers
Environments where robots, and particularly UAS, operate normally contain uncertain and varying parameters. Additionally, robots may malfunction under some circumstances.
To enable a safe operation of robots in such scenarios, Infinium Robotics is developing its own adaptive and fault-tolerant controllers, which can adapt to uncertain and time varying parameters such as wind disturbances, payload changing conditions, motor failure and similar. Such algorithms have been integrated into proprietary autopilot systems and evaluated in real-time.