A deep learning approach for direction of arrival estimation using automotive-grade ultrasonic sensors

Abstract In this paper, a deep learning approach is presented for direction of arrival estimation using automotive-grade ultrasonic sensors which are used for driving assistance systems such as automatic parking. A study and implementation of the state of the art deterministic direction of arrival estimation algorithms is used as a benchmark for the performance of the proposed approach. Analysis of the performance of the proposed algorithms against the existing algorithms is carried out over simulation data as well as data from a measurement campaign done using automotive-grade ultrasonic sensors. Both sets of results clearly show the superiority of the proposed approach under realistic conditions such as noise from the environment as well as eventual errors in measurements. It is demonstrated as well how the proposed approach can overcome some of the known limitations of the existing algorithms such as precision dilution of triangulation and aliasing

Interactive System for Package Delivery in Pedestrian Areas Using a Self-Developed Fleet of Autonomous Vehicles

In the context of automation and digitalization technologies and due to the existing trends of re-urbanization, autonomous vehicles for execution of services such as package delivery, transportation, vegetation care and street cleaning are considered innovative solutions. This paper presents a concept and implementation of a system developed to plan and deliver packages within pedestrian areas, using autonomous vehicles. The novelty of the system lies in the systematic view of this use case, which considers all stakeholder views from the CEP (courier, express, and parcel services) provider, traffic participants, and customers and where the technical and technological innovation is guided by interactivity with the users. This work outlines the design and integration of user interaction, the developed vehicles within the fleet designed for operating within pedestrian environments, and localization and navigation strategies. After the vehicles were approved and certified from a technical point of view to operate in pedestrian areas, the entire system was tested and evaluated in a new city district of Heilbronn with approximately 800 inhabitants. In the last six weeks of experiments, 572 packages were delivered in an autonomous way. The interactive way of planning and executing services on demand led, according to a market study in Heilbronn, to an increased acceptance of the users for autonomous package delivery services from 76% to 91%

Towards Benchmarking of Domestic Robotic Assistants

As service robotics research advances rapidly, availability of objective, reproducible test specifications and evaluation criteria and also of benchmarking is more and more felt to be desirable in the community. As a first step towards benchmarking, in this paper we propose a formalization of tests - exemplified for domestic grasp&place tasks. The underlying philosophy of our approach is to confront the robot system in a black-box manner with requirements of a “rational customer”, and characterize the performance of the system in an objective way by the outcomes of a test-suite tailored to this scenario. A formalized single test description consists of a clear and reproducible specification of the robot’s task and the full context on the one hand, and a number of figures which objectively characterize the test result on the other hand. We illustrate this methodology for the domestic assistance scenario