As part of the FARSCOPE CDT program I worked in a team to develop a solution to Amazon’s picking challenge. This involved designing a robotic pick-and-place system that was capable of recognising and grasping both known and novel objects in cluttered environments.
An application was designed following the model-view-controller architecture to enable multiple autonomous vehicle algorithms to be simulated in different views and to allow the input parameters to be altered in run time e.g. adaptive threshold parameters, coordinates for inverse perspective mapping, number of sample points etc. The code will run slower due to the MVC architecture.
This project involved developing algorithms capable of localising a robot within a known environment but at an unknown position and moving it to a target location. This was achieved in simulation using the BotSim library in Matlab and then implemented onto a real robot.
This project involved developing distributed software enabling a swarm of fixed wing UAVs to track a pollutant cloud. A discrete time state space model of the world was produced and a finite state machine was used to add intelligence.