# Team NimbRo at MBZIRC 2017: Fast Landing on a Moving Target and Treasure Hunting with a Team of MAVs

arXiv: https://arxiv.org/abs/1811.05471 · HTML: https://mlsanity.com/paper/1811.05471/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Nov 2018.

## Built on by (most cited first, 3 of 3)

- [Real-Time Ellipse Detection for Robotics Applications](https://mlsanity.com/paper/2102.12670/) (2021)
- [Brain over Brawn: Using a Stereo Camera to Detect, Track, and Intercept a Faster UAV by Reconstructing the Intruder's Trajectory](https://mlsanity.com/paper/2107.00962/) (2021)
- [Autonomous Aerial Robot for High-Speed Search and Intercept Applications](https://mlsanity.com/paper/2112.05465/) (2021)

## Abstract (arXiv)

The Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2017 has defined ambitious new benchmarks to advance the state-of-the-art in autonomous operation of ground-based and flying robots. This article covers our approaches to solve the two challenges that involved micro aerial vehicles (MAV). Challenge 1 required reliable target perception, fast trajectory planning, and stable control of an MAV in order to land on a moving vehicle. Challenge 3 demanded a team of MAVs to perform a search and transportation task, coined "Treasure Hunt", which required mission planning and multi-robot coordination as well as adaptive control to account for the additional object weight. We describe our base MAV setup and the challenge-specific extensions, cover the camera-based perception, explain control and trajectory-planning in detail, and elaborate on mission planning and team coordination. We evaluated our systems in simulation as well as with real-robot experiments during the competition in Abu Dhabi. With our system, we-as part of the larger team NimbRo-won the MBZIRC Grand Challenge and achieved a third place in both subchallenges involving flying robots.