相关论文: An Approach for Self-Adaptive Path Loss Modeling f…

Some mobile sensor network applications require the sensor nodes to transfer their trajectories to a data sink. This paper proposes an adaptive trajectory (lossy) compression algorithm based on compressive sensing. The algorithm has two…

Achieving top-notch performance in Intelligent Transportation detection is a critical research area. However, many challenges still need to be addressed when it comes to detecting in a cross-domain scenario. In this paper, we propose a…

Ray tracing (RT) simulations require accurate transmitter (TX) and receiver (RX) location information from real-world measurements to accurately characterize wireless propagation behavior in an environment. Such wireless propagation…

This study presents a new methodology for learning-based motion planning for autonomous exploration using aerial robots. Through the reinforcement learning method of learning through trial and error, the action policy is derived that can…

Efficient data collection methods play a major role in helping us better understand the Earth and its ecosystems. In many applications, the usage of unmanned aerial vehicles (UAVs) for monitoring and remote sensing is rapidly gaining…

This paper considers sequential adaptive estimation of sparse signals under a constraint on the total sensing effort. The advantage of adaptivity in this context is the ability to focus more resources on regions of space where signal…

On construction sites, progress must be monitored continuously to ensure that the current state corresponds to the planned state in order to increase efficiency, safety and detect construction defects at an early stage. Autonomous mobile…

We present a method for solving the coverage problem with the objective of autonomously exploring an unknown environment under mission time constraints. Here, the robot is tasked with planning a path over a horizon such that the accumulated…

Predicting pathloss by considering the physical environment is crucial for effective wireless network planning. Traditional methods, such as ray tracing and model-based approaches, often face challenges due to high computational complexity…

Self-supervised monocular depth estimation has become an appealing solution to the lack of ground truth labels, but its reconstruction loss often produces over-smoothed results across object boundaries and is incapable of handling occlusion…

In this paper, we address the problem of adaptive path planning for accurate semantic segmentation of terrain using unmanned aerial vehicles (UAVs). The usage of UAVs for terrain monitoring and remote sensing is rapidly gaining momentum due…

The aim of this paper is to propose a least mean squares (LMS) strategy for adaptive estimation of signals defined over graphs. Assuming the graph signal to be band-limited, over a known bandwidth, the method enables reconstruction, with…

In this paper we propose a highly efficient and very accurate deep learning method for estimating the propagation pathloss from a point $x$ (transmitter location) to any point $y$ on a planar domain. For applications such as user-cell site…

Reconfigurable intelligent surfaces (RISs) provide an interface between the electromagnetic world of wireless propagation environments and the digital world of information science. Simple yet sufficiently accurate path loss models for RISs…

Aerial telecommunications networks based on Low Altitude Platforms (LAPs) are expected to optimally meet the urgent needs of emergency relief and recovery operations for tackling large scale natural disasters. The energy efficient operation…

A robust and accurate positioning solution is required to increase the safety in GPS-denied environments. Although there is a lot of available research in this area, little has been done for confined environments such as tunnels. Therefore,…

IP Geolocation is a key enabler for the Future Internet to provide geographical location information for application services. For example, this data is used by Content Delivery Networks to assign users to mirror servers, which are close…

Perception algorithms that provide estimates of their uncertainty are crucial to the development of autonomous robots that can operate in challenging and uncontrolled environments. Such perception algorithms provide the means for having…

Wireless underground sensor networks play an important role in underground sensing such as climate-smart agriculture and underground infrastructure monitoring. Existing works consider a static underground environment, which is not practical…

Ground robots require the crucial capability of traversing unstructured and unprepared terrains and avoiding obstacles to complete tasks in real-world robotics applications such as disaster response. When a robot operates in off-road field…