Brief description of functionality/utility:
The Lancaster team has developed a system that can be paired with a drone to accurately locate and map a contaminated
area when large external disturbances are experienced, for instance during bad weather.
The system uses a cascaded two-stage modified fast simultaneous localisation and mapping system (SLAM). The technology
was developed for resilient and autonomous navigation by a single drone in an unknown and environment where GPS does
This new navigation system allows the robot to operate reliably over a long period of time when it is sent to a sensory
degraded environment, such as a highly contaminated radioactive environment. It has been evaluated and tested in a realistic
simulation environment using the ROS platform (TRL 2), and implemented on an open-architecture drone system (designed
and built fully at Lancaster University) for laboratory testing (TRL 3). Preliminary work to extend the results to cooperative
robots is ongoing with the support of the National Nuclear Lab.
System key points include:
- High-performance manipulator positioning controllers based on data-driven, stochastic state-dependent parameter
- Addresses uncertainty arising from sensor degradation, material inconsistencies, device nonlinearities, etc.
- Illustrative case study – dual manipulator, semi-autonomous pipe cutting with reciprocating saw.
- Suite of widely applicable algorithms for adaptive control, inverse kinematics, planning
and robot parameter estimation.
- Additional illustrative case study
- identification and control of aerial vehicles with unknown inertia parameters.