An evaluation framework for stereo-based driver assistance

This is the post-print version of the Article - Copyright @ 2012 Springer VerlagThe accuracy of stereo algorithms or optical flow methods is commonly assessed by comparing the results against the Middlebury database. However, equivalent data for automotive or robotics applications rarely exist as they are difficult to obtain. As our main contribution, we introduce an evaluation framework tailored for stereo-based driver assistance able to deliver excellent performance measures while circumventing manual label effort. Within this framework one can combine several ways of ground-truthing, different comparison metrics, and use large image databases. Using our framework we show examples on several types of ground truthing techniques: implicit ground truthing (e.g. sequence recorded without a crash occurred), robotic vehicles with high precision sensors, and to a small extent, manual labeling. To show the effectiveness of our evaluation framework we compare three different stereo algorithms on pixel and object level. In more detail we evaluate an intermediate representation called the Stixel World. Besides evaluating the accuracy of the Stixels, we investigate the completeness (equivalent to the detection rate) of the StixelWorld vs. the number of phantom Stixels. Among many findings, using this framework enables us to reduce the number of phantom Stixels by a factor of three compared to the base parametrization. This base parametrization has already been optimized by test driving vehicles for distances exceeding 10000 km

Scenario-Driven Search for Pedestrians aimed at Triggering Non-Reversible Systems

Abstract-This paper presents the results of an innovative approach to pedestrian detection for automotive applications in which a non-reversible system is used; therefore the aim is to reach a very low false detection rate, ideally zero, by searching for pedestrians in specific areas only. The great advantages of such an approach are that pedestrian recognition is performed on limited image areas-therefore boosting its timing performance- and no assessment on the danger level is finally required before providing the result to either the driver or an on-board computer for automatic manoeuvres. This system has been extensively tested on two prototype vehicles equipped with one laserscanner, one camera, and brakeby-wire technology both in Italy and Korea; this paper describes the extensive tests and shows performance measurements. I

Developing a person guidance module for hospital robots

This dissertation describes the design and implementation of the Person Guidance Module (PGM) that enables the IWARD (Intelligent Robot Swarm for attendance, Recognition, Cleaning and delivery) base robot to offer route guidance service to the patients or visitors inside the hospital arena. One of the common problems encountered in huge hospital buildings today is foreigners not being able to find their way around in the hospital. Although there are a variety of guide robots currently existing on the market and offering a wide range of guidance and related activities, they do not fit into the modular concept of the IWARD project. The PGM features a robust and foolproof non-hierarchical sensor fusion approach of an active RFID, stereovision and cricket mote sensor for guiding a patient to the X-ray room, or a visitor to a patient’s ward in every possible scenario in a complex, dynamic and crowded hospital environment. Moreover, the speed of the robot can be adjusted automatically according to the pace of the follower for physical comfort using this system. Furthermore, the module performs these tasks in any unconstructed environment solely from a robot’s onboard perceptual resources in order to limit the hardware installation costs and therefore the indoor setting support. Similar comprehensive solution in one single platform has remained elusive in existing literature. The finished module can be connected to any IWARD base robot using quick-change mechanical connections and standard electrical connections. The PGM module box is equipped with a Gumstix embedded computer for all module computing which is powered up automatically once the module box is inserted into the robot. In line with the general software architecture of the IWARD project, all software modules are developed as Orca2 components and cross-complied for Gumstix’s XScale processor. To support standardized communication between different software components, Internet Communications Engine (Ice) has been used as middleware. Additionally, plug-and-play capabilities have been developed and incorporated so that swarm system is aware at all times of which robot is equipped with PGM. Finally, in several field trials in hospital environments, the person guidance module has shown its suitability for a challenging real-world application as well as the necessary user acceptance

Vision Based Vehicle Localization for Infrastructure Enabled Autonomy

Primary objective of this research is to devise techniques to localize an autonomous vehicle in an Infrastructure Enabled Autonomy (IEA) setup. IEA is a new paradigm in autonomous vehicles research that aims at distributed intelligence architecture by transferring the core functionalities of sensing and localization to infrastructure. This paradigm is also promising in designing large scalable systems that enable autonomous car platooning on highways. A reliable camera calibration technique for such an experimental setup is discussed, followed by the technique for 2D image to 3D world coordinate transformation. In this research, information is received from: (1) on-board vehicle sensors like GPS and IMU, (2) localized car position data derived from deep learning on the real-time camera feeds and (3) lane detection data from infrastructure cameras. This data is fused together utilizing an Extended Kalman Filter (EKF) to obtain reliable position estimates of the vehicle at 50 Hz. This position information is then used to control the vehicle with an objective of following a prescribed path. Extensive simulation and experimental results are also presented to corroborate the performance of the proposed approach