Frontally placed eyes versus laterally placed eyes: computational comparison of their functions for ego-motion estimation

Both frontally placed eyes and laterally placed eyes are popular in nature, and although which one is better could be one of the most intuitive questions to ask, it could also be the hardest question to answer. Their most obvious difference is that, at least as supposed in the computer vision community, stereopsis plays the central role in the visual system composed of frontally placed eyes (or cameras); however, it is not available in the lateral configuration due to the lack of overlap between the visual fields. As a result, researchers have adopted completely different approaches to model the two configurations and developed computational mimics of them to address various vision problems. Recently, the advent of novel quasi-parallax conception unifies the ego-motion estimation procedure of these two eye configurations into the same framework and makes systematic comparison feasible. In this paper, we intend to establish the computational superiority of eye topography from the perspective of ego-motion estimation. Specifically, quasi-parallax is applied to fuse motion cues from individual cameras at an early stage, at the pixel level, and to recover the translation and rotation separately with high accuracy and efficiency without the need of feature matching. Furthermore, its applicability on the extended sideways arrangements is studied successfully to make our comparison more general and insightful. Extensive experiments on both synthetic and real data have been done, and the computational superiority of the lateral configuration is verified.

Sensor for distance measurement using pixel grey-level information

An alternative method for distance measurement is presented, based on a radiometric approach to the image formation process. The proposed methodology uses images from an infrared emitting diode (IRED) to estimate the distance between the camera and the IRED. Camera output grey-level intensities are a function of the accumulated image irradiance, which is also related by inverse distance square law to the distance between the camera and the IRED. Analyzing camera-IRED distance, magnitudes that affected image grey-level intensities, and therefore accumulated image irradiance, were integrated into a differential model which was calibrated and used for distance estimation over a 200 to 600 cm range. In a preliminary model, the camera and the emitter were aligned.

The AGROBOT project

The aim of this paper is to illustrate the AGROBOT project. This project was initiated to develop a complete robotic system for the production cycle of tomato plants in a greenhouse environment. The robot architecture is based on a vehicle carrying the picking arm (a six degrees of freedom anthropomorphic arm with a gripper/hand), the head with the two micro cameras (for the color stereoscopic vision system) and the VME rack for the complete control of the system. The head was purposely developed to permit complete visibility of the overall area. The vision system drives the head to point the path during navigation or to explore the plants looking for the work objects. The robot will be able to navigate between rows of plants, stop near each plant and identify the relevant objects (fruits or flowers) so as to be able to pick ripe tomatoes or spray anticryptogamic substances on flowers. Due to its flexible architecture, the system can be suited to operate on other kinds of cultivation or could be modified to perform other kinds of operations such as transplanting or packaging. Also the field of action could be different from greenhouses: changing from a wheeled locomotion system to a tracked system, the robot will be able to operate on particularly irregular surfaces. These features make this robotic system particularly adapted to replace human from tiring and harmful tasks or operating within adverse environment.