Collaborative 3D Reconstruction Using Heterogeneous UAVs: System and Experiments

  title={Collaborative 3D Reconstruction Using Heterogeneous UAVs: System and Experiments},
  author={Timo Hinzmann and Thomas Stastny and Gianpaolo Conte and Patrick Doherty and Piotr Rudol and Mariusz Wzorek and Enric Galceran and Roland Y. Siegwart and Igor Gilitschenski},
  booktitle={International Symposium on Experimental Robotics},
This paper demonstrates how a heterogeneous fleet of unmanned aerial vehicles (UAVs) can support human operators in search and rescue (SaR) scenarios. We describe a fully autonomous delegation framework that interprets the top-level commands of the rescue team and converts them into actions of the UAVs. In particular, the UAVs are requested to autonomously scan a search area and to provide the operator with a consistent georeferenced 3D reconstruction of the environment to increase the… 

Collaborative UAV-UGV Environment Reconstruction in Precision Agriculture

This paper proposes a novel maps registration pipeline that leverages a digital multi-modal environment representation which includes a vegetation index map and a Digital Surface Model (DSM) and casts the data association problem between maps built from UAVs and UGVs as a multi- modal, large displacement dense optical flow estimation.

AgriColMap: Aerial-Ground Collaborative 3D Mapping for Precision Farming

AgriColMap is proposed, a novel map registration pipeline that leverages a grid-based multimodal environment representation, which includes a vegetation index map and a digital surface model that outperforms several state-of-the-art map registration and matching techniques by a large margin.

Segment-based Cross-domain Localization between Aerial and Ground Robots

This work presents a segment-based cross-domain localization solution that accurately calculates the pose of a UGV in the reference map generated by a UAV, and achieves notable better performance than the baseline method SegMap.

Toward Aerial and Ground Robots Collaboration for 3D Map Building in Precision Agriculture

This paper tackles the problem of fuse data from heterogeneous robots by proposing a novel registration pipeline that leverages semantic information extracted from image-based 3D reconstructions of the target environment, and performs the alignment exploiting only meaningful parts of the recorded data.

3D registration of aerial and ground robots for disaster response: An evaluation of features, descriptors, and transformation estimation

This work extensively evaluate different approaches to globally register UGV generated 3D point-cloud data from LiDAR sensors with UAV generated point- Cloud maps from vision sensors to help the community take informed decisions when registering point- cloud maps from ground robots to those from aerial robots.

Evaluation of 3D LiDAR Sensor Setup for Heterogeneous Robot Team

A collaborative mapping framework for heterogeneous robot teams to make full use of collected information from different viewpoints and explore large areas more efficiently is proposed and was shown to work more efficiently compared with existing methods.

Heuristics for optimizing 3D mapping missions over swarm-powered ad-hoc clouds

This work presents a mathematical programming heuristic based on decomposition and a variable neighborhood search heuristic to minimize the completion time of the 3D reconstruction process necessary in swarming-powered distributed 3D mapping missions.

A Collaborative Framework for 3D Mapping Using Unmanned Aerial Vehicles

An overview of a generic framework for collaboration among humans and multiple heterogeneous robotic systems based on the use of a formal characterization of delegation as a speech act for 3D reconstruction in alpine environments intended to be used by alpine rescue teams is described.

WARA-PS: a research arena for public safety demonstrations and autonomous collaborative rescue robotics experimentation

A research arena (WARA-PS) for sensing, data fusion, user interaction, planning and control of collaborative autonomous aerial and surface vehicles in public safety applications is presented. The

The current state and future outlook of rescue robotics

The current state of the art in ground and aerial robots, marine and amphibious systems, and human–robot control interfaces are surveyed and the readiness of these technologies with respect to the needs of first responders and disaster recovery efforts is assessed.



A Collaborative Framework for 3D Mapping Using Unmanned Aerial Vehicles

An overview of a generic framework for collaboration among humans and multiple heterogeneous robotic systems based on the use of a formal characterization of delegation as a speech act for 3D reconstruction in alpine environments intended to be used by alpine rescue teams is described.

Long-Endurance Sensing and Mapping Using a Hand-Launchable Solar-Powered UAV

An endurance analysis shows that AtlantikSolar can provide full-daylight operation and a minimum flight endurance of 8 h throughout the whole year with its full multi-camera mapping payload.

High-Level Mission Specification and Planning for Collaborative Unmanned Aircraft Systems Using Delegation

An agent-based software architecture, a temporal logic-based mission specification language, a distributed temporal planner and a task specification language that when integrated provide a basis for the generation, instantiation and execution of complex collaborative missions on heterogeneous air vehicle systems.

Robust state estimation for small unmanned airplanes

A multi-sensor fusion framework based on Extended Kalman Filtering (EKF) which is light-weight enough to run on-board small unmanned airplanes using measurements from a MEMS based Inertial Measurement Unit, static and dynamic pressure sensors, as well as GPS (position and velocity) and a 3D magnetic compass.

Comparing ICP variants on real-world data sets

A protocol that allows for a comparison between ICP variants, taking into account a broad range of inputs, and an open-source ICP library, which is fast enough to be usable in multiple real-world applications, while being modular enough to ease comparison of multiple solutions.

The normal distributions transform: a new approach to laser scan matching

  • P. BiberW. Straßer
  • Computer Science
    Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453)
  • 2003
First results on real data demonstrate, that the normal distributions transform algorithm is capable to map unmodified indoor environments reliable and in real time, even without using odometry data.

Point Clouds Registration with Probabilistic Data Association

This work proposes an improvement over the standard ICP data association policy and it is called Probabilistic Data Association, derived applying statistical inference techniques on a fully probabilistic model to deal with the problem of dense-sparse registration.

Evaluation of a Light-weight Lidar and a Photogrammetric System for Unmanned Airborne Mapping Applications : [Bewertung eines Lidar-systems mit geringem Gewicht und eines photogrammetrischen Systems für Anwendungen auf einem UAV]

A comparison of two light-weight and low-cost airborne mapping systems based on a lidar technology and the other on a video camera is presented.

Iterative point matching for registration of free-form curves and surfaces

  • Zhengyou Zhang
  • Computer Science
    International Journal of Computer Vision
  • 2005
A heuristic method has been developed for registering two sets of 3-D curves obtained by using an edge-based stereo system, or two dense3-D maps obtained by use a correlation-based stereoscopic system, and it is efficient and robust, and yields an accurate motion estimate.