Leaky Integrate Neuron Model for Multi Robot Task Allocation
The evolution of methodologies in Multi Robot Task Allocation is surveyed. Various classifications of Taxonomy in the domain is compared to the relevance of its application. An idea for a novel ‘Leaky Integrate and Fire’ Neuron Model for Multi Robot Task Allocation is presented along with the explanation of its biological theory. This is used as an inspiration to model a setup of heterogenous autonomous Multi Robot system in a farmland environment. The model would be simulated as a software using Python. Performance of the system will be evaluated and compared to that of a traditional Market based approach. Findings shall be drawn and Results are to be summarised.
Fleet Management of Autonomous Agricultural Robots with Human Awareness
Fleet management of autonomous agricultural robots is fundamental to fully autonomous farming practices as it addresses the issues of conflict resolution, resource and efficiency optimisation when dealing with a fleet of homogenous or heterogenous robots. The abstract of the proposal for this PhD would be integrating human behaviour models with the navigation and task allocation system of autonomous fleets for better path planning evading possible conflicts and deadlock situations between robot-robot and human-robot(s). The study will focus on the proxemics, human behaviour modelling using decision prediction and neuroscientific methods, path planning, fleet coordination and human robot ethics.