Category: ‘TRADR’

TRADR at 2017 European Robotics Forum Workshop on S&R Robots

22 March, 2017 Posted by tradr_admin

 

 

Ivana Kruijff-Korbayová and Hartmut Surmann (re)presented TRADR at the European Robotics Forum in Edinburgh, March 22-24 2017. In the session “Success Stories: Robotics for Disaster Response” Ivana spoke about TRADR objectives and recent results, including the deployment of TRADR robots in response to the earthquake in Amatrice. Alongside speakers from several other EU projects dealing with disaster response and search & rescue she was also one of the panelists in a discussion which addressed S&R competitions, involvement of companies, benchmarking and system integration.
In the AI & Cognitive Robotics session “AI for long-term autonomy in robot applications” Ivana delivered a position statement based on TRADR experience and participated in group discussions. Similarly to the speakers representing other domains of application she underlined the need for learning from experience, e.g., to avoid repeating a mistake; the need for coping with complex, unknown, unpredictable and dynamic environments; and the need for communication between robots and humans about mission progress, including environment changes.

TRADR Year 3 Review in Montelibretti, Italy

7 March, 2017 Posted by tradr_admin

The TRADR Year 3 review took place at the Scuola Di Formazione Operativa in Montelibretti, (Italy) of Vigili del Fuoco on Tuesday March 7 and Wednesday March 8.
The system demonstration was successful and the overall progress of the project was evaluated by the predicate “excellent” or “very good”.
More detailed information will follow soon.

 

Curves repository is now public

3 February, 2017 Posted by tradr_admin

The objective of the TRADR project is to enable a team of humans and robots to collaborate in a disaster response scenario which can last over several days. To achieve this, one of the core capabilities of the robots is their capacity to create a 3D map of their environment and to localize themselves within this map.

The TRADR consortium has recently open-sourced three libraries with the purpose of enabling robots equipped with 3D laser scanners to perform the above mentioned tasks. The curves library is used to represent the robot’s continuous-time trajectory in 3D space while the laser_slam library implements the back-end estimation functionalities of the localization and mapping system. The SegMatch library finally enables the robots to recognize previously visited places and to transmit this information to the back-end in order to close loops and to register trajectories of different robots.

Links to libraries:

https://github.com/ethz-asl/curves
https://github.com/ethz-asl/laser_slam
https://github.com/ethz-asl/segmatch

The following figure illustrates a map which was generated by fusing 3D laser scanner measurements from two unmanned ground vehicles which were collected during the TRADR Evaluation exercise at the Gustav Knepper Power Station in Dortmund, Germany. The map is coloured by height and the robot trajectories are represented as blue and red lines.

For more information about the place recognition algorithm please consult our paper (https://arxiv.org/pdf/1609.07720v1.pdf) and have a look at our video (https://www.youtube.com/watch?v=iddCgYbgpjE). Easy to run demonstrations can be found in the wiki page of the SegMatch repository. More to come!

Best SSRR 2016 Late Breaking Report Award

1 November, 2016 Posted by tradr_admin

Team members of TRADR received the Best Late Breaking Report Award at the International Symposium on Safety, Security and Rescue Robotics (SSRR) 2016 for their work titled “3D Localization, Mapping and Path Planning for Search and Rescue Operations”. The report issued from a collaboration with the Alcor Lab from the Sapienza University of Rome and presented results obtained at the third Joint Exercise of the FP7 TRADR project.

 

Third TRADR Evaluation Exercise

29 October, 2016 Posted by tradr_admin

The yearly TRADR Evaluation exercise (T-Eval) took place end October 2016 in Dortmund, Germany. The location was an old coal-fired power plant `Knepper’ in Dortmund, a large industrial complex which offered multiple stories, obstacles and rubble and allowed for indoor UAV flying.

 

 

Together with end-users from the fire department of the city of Dortmund, a number of disaster response exercises were enacted in which the TRADR system was used to provide robotic response.

Mission objectives included scanning of the environment and creation of maps enabling autonomous UGV navigation, multi-robot patrolling and searching for Points of Interest, such as smoke, fire and victims.

In addition, the robotic arm mounted on the UGVs was used to retrieve a chemical sample from the disaster environment. The exercises were successful and will contribute to a further improvement and refinement of the TRADR system in Year 4 of the project.