Wednesday 21 May 2025
A recent innovation in robotics has made it possible for multiple unmanned aerial vehicles (UAVs) to navigate and localize themselves indoors using a combination of ultra-wideband (UWB) radio signals and computer vision.
The new dataset, called MILUV, provides researchers and developers with a wealth of information about the performance of UWB-based localization systems in various indoor environments. The dataset includes data from three quadcopters equipped with custom-made UWB transceivers, stereo cameras, inertial measurement units (IMUs), and magnetometers.
The UWB transceivers are capable of transmitting radio signals at a frequency of 3-10 GHz, which allows for high-resolution ranging measurements to be taken. The computer vision component uses a stereo camera system to capture images of the environment, which can then be used to estimate the position and orientation of the UAVs.
The dataset includes a range of different experiments, each with varying numbers of UAVs, UWB tags, environments, and motion profiles. This allows researchers to test and evaluate their algorithms in a variety of scenarios, from simple indoor navigation to complex multi-robot systems.
One of the key challenges in developing UWB-based localization systems is dealing with multipath interference, which occurs when radio signals bounce off surfaces and arrive at the receiver at different times. The MILUV dataset includes data on the effects of multipath interference on ranging measurements, allowing researchers to develop more robust algorithms for mitigating these effects.
The dataset also includes data from a motion capture system, which provides ground truth information about the position and orientation of each UAV. This allows researchers to evaluate the accuracy of their localization algorithms and identify areas where improvements can be made.
The availability of this dataset has significant implications for the development of autonomous systems, such as delivery drones or search-and-rescue robots. By enabling multiple UAVs to navigate and localize themselves indoors using UWB radio signals and computer vision, MILUV opens up new possibilities for complex multi-robot missions.
In addition to its applications in robotics, the MILUV dataset has potential uses in other fields, such as surveying and mapping. For example, it could be used to develop more accurate methods for creating 3D models of indoor environments or monitoring the movement of objects over time.
Overall, the MILUV dataset represents a significant step forward in the development of UWB-based localization systems and has the potential to enable new applications in a range of fields.
Cite this article: “Multicopter Indoor Localization Using Ultra-Wideband Radio Signals and Computer Vision (MILUV)”, The Science Archive, 2025.
Uavs, Uwb, Localization, Computer Vision, Robotics, Indoor Navigation, Multipath Interference, Motion Capture, Autonomous Systems, Surveying
