Biologically Inspired Vision for Indoor Robot Navigation

Ultrasonic, infrared, laser and other sensors are being applied in robotics. Although combinations of these have allowed robots to navigate, they are only suited for specific scenarios, depending on their limitations. Recent advances in computer vision are turning cameras into useful low-cost sensors that can operate in most types of environments. Cameras enable robots to detect obstacles, recognize objects, obtain visual odometry, detect and recognize people and gestures, among other possibilities. In this paper we present a completely biologically inspired vision system for robot navigation. It comprises stereo vision for obstacle detection, and object recognition for landmark-based navigation. We employ a novel keypoint descriptor which codes responses of cortical complex cells. We also present a biologically inspired saliency component, based on disparity and colour.

Multiuser Detection for the Uplink of Prefix-Assisted DS-CDMA Systems Employing Multiple Transmit and Receive Antennas

In this paper we consider the uplink transmission within a DS-CDMA system employing CP-assisted (Cylic Prefix) block transmission techniques combined with spatial multiplexing techniques that require multiple antennas at both the transmitter and the receiver. We present an efficient frequency-domain receiver structure with iterative MUD (MultiUser Detection). The performance of the proposed receiver can be close to the single user matched filter bound, even for fully loaded systems and/or severely time-dispersive channels.