Resource-adaptive Control for Resource-constrained Robot Using Dynamic Reconfiguration of FPGA

This paper presents resource-adaptive control which is a new scheme to change control parameters for resource-constrained robots using FPGA reconfiguration. Small-scale robots impose constraints on resources such as power or space for modules, but they still require great functionality to do challenging tasks such as surveillance, urban search and rescue, application specific sensing, robotic assembly, etc. This paper develops a reconfigurable computing platform for small-scale resource constrained robots. Resource-adaptive control is introduced where control parameters can be changed with respect to the resource usage such as power consumption, area, or execution speed, as well as plant change. The use of a Field Programmable Gate Array (FPGA) is essential in providing the flexibility in hardware for both sensor interfacing and hardware-accelerated computation in this research. Dynamic reconfiguration or run-time reconfiguration is performed in order to maximize the resource utilization in terms of power, area and speed while the robot is executing tasks. A software architecture for hardware/software dynamic reconfigurability is proposed and it provides for the reallocation of hardware and software resources at run time as the mobile, resource-constrained robots encounter unknown environmental conditions that render various sensors ineffective. A novel strategy to search a configuration tree is presented and metrics for cost functions in the tree are introduced. Resource-adaptive controller can modify control parameters, or change the order of a plant model, or even choose a different control algorithm by examining resource utilization during dynamic reconfiguration.