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Error-State Unscented Kalman-Filter for UAV Indoor Navigation | IEEE Conference Publication | IEEE Xplore

Error-State Unscented Kalman-Filter for UAV Indoor Navigation


Abstract:

In this paper, we present an algorithm for indoor quadcopter navigation. We implemented a strapdown navigation algorithm combined with an error-state unscented Kalman-Fil...Show More

Abstract:

In this paper, we present an algorithm for indoor quadcopter navigation. We implemented a strapdown navigation algorithm combined with an error-state unscented Kalman-Filter capable of fusing IMU, barometer and UWB measurements. Optical flow and distance to ground measurements are additionally fused to further improve the state estimation quality. Compared to alternate approaches, the suggested algorithm has better trajectory following abilities and does not rely on the actual quadcopter's dynamics, so it can be applied to a variety of flying platforms. We implemented and evaluated the algorithm on the Crazyflie 2.1 nano-quadcopter.
Date of Conference: 04-07 July 2022
Date Added to IEEE Xplore: 09 August 2022
ISBN Information:
Conference Location: Linköping, Sweden

I. Introduction

Mobile robots and especially quadcopters offer new possibilities in research and in commercial applications. Exemplary applications include their use as a mobile sensor platform, in search and rescue [17], exploration tasks and in logistics [1]. For indoor navigation, ultra-wide band (UWB) based time-difference of arrival (TDoA) measurements [3], [12], [18] and potentially optical flow and laser-based altitude measurements [5] can be used by quadcopters to position themselves within an indoor environment. A major advantage of the UWB measurements is that these signals have good penetration capabilities, so positioning is possible within obstructed environments. For a higher accuracy in navigational performance, motion capture system (MoCap) or the Lighthouse Positioning System [15] are also a possibility. However, these types of systems are constrained to applications with non-obstructed line-of-sight contact to their transmitting devices. For applications such as multi-agent path coordination in obstructed environments, a satisfactory navigation performance is of crucial importance, but line-of-sight contact to the transmitting devices can not be guaranteed. Therefore, it is of importance to improving the UWB-based navigation performance.

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References

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