Chen Zhu

A swarm of robots offers significant advantages over a single robot, enabling faster exploration of larger areas and enhanced robustness against single-point failures. Accurate relative positioning is critical for executing collaborative missions without collisions. When Visual Simultaneous Localization and Mapping (VSLAM) is employed to estimate each robot’s poses, the inter-agent loop closing method is commonly used to improve relative positioning accuracy by refining pose estimates and merging local maps based on shared feature points. However, this approach demands considerable computational and communication resources. In this paper, we introduce Collaborative SLAM using Visual Odometry and Ranges (CoVOR-SLAM) to address these challenges. CoVOR-SLAM significantly reduces both the amount of data transmitted between robots and their computational loads, as it requires only pose estimates, covariances, and range measurements instead of feature or map points for inter-agent loop detection. The necessary range measurements can be derived from pilot signals within the communication system, eliminating the need for complex additional infrastructure. We evaluated CoVOR-SLAM using real images and ultra-wideband range data collected from two rovers, as well as in a larger multi-agent setup utilizing public image datasets and realistic simulations. The results demonstrate that CoVOR-SLAM accurately estimates robot poses while requiring considerably less computational power and communication capacity than inter-agent loop closing techniques.

Communication, Navigation and Surveillance (CNS) technologies are key enablers for future safe operation of drones in urban environments. However, the design of navigation technologies for these new applications is more challenging compared to e.g., civil aviation. On the one hand, the use cases and operations in urban environments are expected to have stringent requirements in terms of accuracy, integrity, continuity and availability. On the other hand, airborne sensors may not be based on high-quality equipment as in civil aviation and solutions need to rely on tighter multisensor solutions, whose safety is difficult to assess. In this work, we first provide some initial navigation requirements related to precision approach operations based on recently proposed vertiport designs. Then, we provide an overview of a possible multisensor navigation architecture solution able to support these types of operations and we comment on the challenges of each of the subsystems. Finally, initial proof of concept for some navigation sensor subsystems is presented based on flight trials performed during the German Aerospace Center (DLR) project HorizonUAM.

Urban Air Mobility (UAM) is a new air transportation system for passengers and cargo in urban environments, enabled by new technologies and integrated into multimodal transportation systems. The vision of UAM comprises the mass use in urban and suburban environments, complementing existing transportation systems and contributing to the decarbonization of the transport sector. Initial attempts to create a market for urban air transportation in the last century failed due to lack of profitability and community acceptance. Technological advances in numerous fields over the past few decades have led to a renewed interest in urban air transportation. UAM is expected to benefit users and to also have a positive impact on the economy by creating new markets and employment opportunities for manufacturing and operation of UAM vehicles and the construction of related ground infrastructure. However, there are also concerns about noise, safety and security, privacy and environmental impacts. Therefore, the UAM system needs to be designed carefully to become safe, affordable, accessible, environmentally friendly, economically viable and thus sustainable. This paper provides an overview of selected key research topics related to UAM and how the German Aerospace Center (DLR) contributed to this research in the project "HorizonUAM - Urban Air Mobility Research at the German Aerospace Center (DLR)". Selected research results on the topics of market potential and public acceptance, vehicle design (including battery degradation, onboard systems, cabin design, cabin simulation), infrastructure, operations (including U-space, safe autonomy, navigation, communication, cost modeling) and overall system modeling are briefly presented.

This paper describes a concept for local GNSS (Global Navigation Satellite System) augmentation derived from the established Ground Based Augmentation System (GBAS) in civil aviation. The aim of this concept is to provide reliable and accurate GNSS measurements for integration into a redundant, safe and reliable integrated navigation architecture tailored to serve Urban Air Mobility (UAM). The proposed concept for local GNSS augmentation addresses the specific challenges of UAM, in particular for take-off and landing operations, and ensures safe separation between UAM vehicles en route between vertiports. By using less expensive hardware compared to the traditional GBAS, the concept aims to make the integration into future urban airspace easier and more cost-effective, both in terms of ground infrastructure demands and on-board navigation hardware. In addition to the high-level system concept and considerations, we present an initial nominal performance assessment of local augmentation using lower-cost airborne and ground hardware. This assessment is based on actual UAV (Unmanned Aerial Vehicle) flight trials conducted in different urban scenarios, as well as long-term rooftop measurements.

Key performance indicators (KPIs) are of great significance in the monitoring of wireless network service quality. The network service quality can be improved by adjusting relevant configuration parameters (CPs) of the base station. However, there are numerous CPs and different cells may affect each other, which bring great challenges to the association analysis of wireless network data. In this paper, we propose an adjustable multi-level association rule mining framework, which can quantitatively mine association rules at each level with environmental information, including engineering parameters and performance management (PMs), and it has interpretability at each level. Specifically, We first cluster similar cells, then quantify KPIs and CPs, and integrate expert knowledge into the association rule mining model, which improve the robustness of the model. The experimental results in real world dataset prove the effectiveness of our method.

The project City-ATM, launched by the German Aerospace Center DLR in 2018, aims to integrate new airspace users like unmanned aerial vehicles into uncontrolled airspace. An air traffic management and traffic flow control concept were developed. The phase 1 demonstration in 2019 showed a bridge inspection featuring, amongst other elements, the flight of several drones in a limited area, beyond visual line of sight operation, strategic flight planning considering strategic geo-fences and tactical conflict detection. To enrich the base concept from phase 1 with more U-Space services, the concept has been extended for phase 2 by dynamic geo-fencing for the tactical avoidance of danger spots. This paper describes how dynamic geo-fences can be modeled around a hazard area, how the dynamic opening and closure of these fences can be distributed to relevant systems, and how the fences are considered by on-ground and already in air vehicles. The complete concept has been implemented and tested at the National Experimental Test Center in Cochstedt. Finally, the execution of successful flight trials is described.

Summary Camera-based visual navigation has great potential for various applications, especially in satellite-signal-degenerated environments. However, the lack of integrity protection has constrained its utilization in safety-critical applications. Integrity characterizes the quality of the information that a navigation system delivers. Integrity frameworks have been developed over decades for satellite navigation, and continue to play an essential role in safety-critical applications like civil aviation. Nevertheless, there are several challenges to quantify the risks associated with visual navigation. Over the last few years, several approaches to tackle these challenges have been investigated. These developments are the first steps toward a reliable visual positioning framework with integrity monitoring capabilities. In this paper, we review the current status, particular challenges, and development trends in visual positioning integrity monitoring. In addition, we propose a preliminary framework so that the future developments on visual navigation integrity can benefit from a systematic approach.