相关论文: iDROP: Robust Localization for Indoor Navigation o…
This paper proposes Drone Squadron Optimization, a new self-adaptive metaheuristic for global numerical optimization which is updated online by a hyper-heuristic. DSO is an artifact-inspired technique, as opposed to many algorithms used…
Current trends in autonomous vehicles and their applications indicates an increasing need in positioning at low battery and compute cost. Lidars provide accurate localization at the cost of high compute and power consumption which could be…
Globally localizing a mobile robot in a known map is often a foundation for enabling robots to navigate and operate autonomously. In indoor environments, traditional Monte Carlo localization based on occupancy grid maps is considered the…
The problem of navigating a formation of interconnected tethered drones, named STEM (System of TEthered Multicopters), in an unknown environment is considered. The tethers feed electrical power from a ground station to the drones and also…
Image retrieval (IR) has emerged as a promising approach for self-localization in unmanned aerial vehicles (UAVs). However, IR-based methods face several challenges: 1) Pre- and post-processing incur significant computational and storage…
Passive geolocation by multiple unmanned aerial vehicles (UAVs) covers a wide range of military and civilian applications including rescue, wild life tracking and electronic warfare. The sensor-target geometry is known to significantly…
Commercial drones are not yet dimensioned to perform indoor autonomous tasks, since they use GPS for their location in the environment. When it comes to a space with physical obstacles (walls, metal, etc.) between the communication of the…
Nanodrone swarm is formulated by multiple light-weight and low-cost nanodrones to perform the tasks in very challenging environments. Therefore, it is essential to estimate the relative position of nanodrones in the swarm for accurate and…
Accurate navigation is of paramount importance to ensure flight safety and efficiency for autonomous drones. Recent research starts to use Deep Neural Networks to enhance drone navigation given their remarkable predictive capability for…
This paper presents a novel approach for aerial drone autonomous navigation along predetermined paths using only visual input form an onboard camera and without reliance on a Global Positioning System (GPS). It is based on using a deep…
We present a novel optimization algorithm called DroNeRF for the autonomous positioning of monocular camera drones around an object for real-time 3D reconstruction using only a few images. Neural Radiance Fields or NeRF, is a novel view…
Quadruped robots are currently a widespread platform for robotics research, thanks to powerful Reinforcement Learning controllers and the availability of cheap and robust commercial platforms. However, to broaden the adoption of the…
Low-altitude wireless networks (LAWN) require drones to follow specific trajectories controlled by ground base stations (GBSs). However, given complex low-altitude channel conditions and limited spectrum and power resources, sensing errors…
Autonomous micro aerial vehicles still struggle with fast and agile maneuvers, dynamic environments, imperfect sensing, and state estimation drift. Autonomous drone racing brings these challenges to the fore. Human pilots can fly a…
With the rapid advance of sophisticated control algorithms, the capabilities of drones to stabilise, fly and manoeuvre autonomously have dramatically improved, enabling us to pay greater attention to entire missions and the interaction of a…
It is often necessary for drones to complete delivery, photography, and rescue in the shortest time to increase efficiency. Many autonomous drone races provide platforms to pursue algorithms to finish races as quickly as possible for the…
This paper explores the potential of 5G new radio (NR) Time-of-Arrival (TOA) data for indoor drone localization under different scenarios and conditions when fused with inertial measurement unit (IMU) data. Our approach involves performing…
Drones are becoming increasingly important in search and rescue missions, and even military operations. While the majority of drones are equipped with camera vision capabilities, the realm of drone audition remains underexplored due to the…
We present the design, implementation, and evaluation of MiFly, a self-localization system for autonomous drones that works across indoor and outdoor environments, including low-visibility, dark, and GPS-denied settings. MiFly performs 6DoF…
This paper proposes a simple strategy for sim-to-real in Deep-Reinforcement Learning (DRL) -- called Roll-Drop -- that uses dropout during simulation to account for observation noise during deployment without explicitly modelling its…