On-Board Vision Processing For Small UAVs: Time to Rethink Strategy

TL;DR

This paper reviews the challenges of implementing onboard vision processing for small UAVs and advocates for hardware-based solutions like FPGAs and ASICs to meet strict size, weight, and power constraints.

Contribution

It analyzes the feasibility of ASICs, Structured ASICs, and FPGAs for onboard vision processing in small UAVs, highlighting potential hardware architectures.

Findings

FPGA-based architectures show promising results for onboard vision processing.

Hardware solutions can address payload and power constraints of small UAVs.

Feasibility analysis supports ASICs and FPGAs as viable options for future UAV systems.

Abstract

The ultimate research goal for unmanned aerial vehicles (UAVs) is to facilitate autonomy of operation. Research in the last decade has highlighted the potential of vision sensing in this regard. Although vital for accomplishment of missions assigned to any type of unmanned aerial vehicles, vision sensing is more critical for small aerial vehicles due to lack of high precision inertial sensors. In addition, uncertainty of GPS signal in indoor and urban environments calls for more reliance on vision sensing for such small vehicles. With off-line processing does not offer an attractive option in terms of autonomy, these vehicles have been challenging platforms to implement vision processing onboard due to their strict payload capacity and power budget. The strict constraints drive the need for new vision processing architectures for small unmanned aerial vehicles. Recent research has shown encouraging results with FPGA based hardware architectures. This paper reviews the bottle necks involved in implementing vision processing on-board, advocates the potential of hardware based solutions to tackle strict constraints of small unmanned aerial vehicles and finally analyzes feasibility of ASICs, Structured ASICs and FPGAs for use on future systems.