Design and Validation of a Camera-Based Safety System for Fenceless Robotic Work Cells

Abstract

A two-dimensional (2-D) camera system with a real-time image processing-based safety technology is a cost-effective alternative that needs optimization of the cell layout, the number of cameras, and the camera's locations and orientations. A design optimization study was performed using the multi-criteria linear fractional programming method and considering the number of cameras, the resolution, as well as camera positions and orientations. A table-top experimental setup was designed and built to test the effectiveness of the optimized design using two cameras. The designs at optimal and nonoptimal parameters were compared using a deep learning algorithm, ResNet-152. To eliminate blind spots, a simple but novel 2-D image merging technique was proposed as an alternative to commonly employed stereo imaging methods. Verification experiments were conducted by using two camera resolutions with two graphic processors under varying illuminance. It was validated that high-speed entrances to the safety system were detected reliably and with a 0.1 s response time. Moreover, the system was proven to work effectively at a minimum illuminance of 120 lux, while commercial systems cannot be operated under 400 lux. After determining the most appropriate 2-D camera type, positions, and angles within the international standards, the most cost-effective solution set with a performance-to-price ratio up to 15 times higher than high-cost 3-D camera systems was proposed and validated.