ADAPT 1st Field Campaign
During the campaign participants were able to evaluate the performance of your robot system and algorithms, in the field of agile production, with respect to assembly and human-robot collaboration. ADAPT benchmarks evaluate robot perception and actions (e.g., object detection, pose estimation, grasping and manipulation and collaborative robot programming). Objects used are 3D printed gear assemblies to be manipulated by any robot and any gripper. More information can be found in the ADAPT evaluation plan.
More information regarding the 2022 1st Field Campaign have been provided at the 2nd ADAPT Workshop on May 6th.
Results announcement
The ADAPT 1st field campaign competition took place from May 6 to June 22 in the form of a video submission track and live demo track. The challenge consisted of the assembly of a helical gear by collaborative programming (TBM1) with human and robot.
The video track received three solution submissions of teams from OFFIS/University of Oldenburg, Germany (team SkillBot), Tampere University, Finland (team TUNI) and University of Padova, Italy (team CURAMI). For the live demo track team SkillBot and CURAMI participated in demonstrating their solutions.
Winners:
Video track
1st place: IAS-Lab Team (University of Padova)
2nd place: SkillBot (OFFIS/UniOL) & TUNI (Tampere University)
Open-source award: TUNI (Tampere University) - https://github.com/KulunuOS/TuniMetricsCompetition
Live demo track
1st place: IAS-Lab Team (University of Padova)
2nd place: SkillBot (OFFIS/UniOL)
Congratulations to the winners!
Team SkillBot (OFFIS/UniOL) – video submission: Augmented Reality assembly programming
Team SkillBot (OFFIS/UniOL)– video submission: Robotic gear assembly on back plate
Team IAS-Lab Team (University of Padova) – video submission: Robotic gear grasping
Team TUNI (Tampere University) – video submission: Robotic gear assembly on back plate
Live demo track: Team IAS-Lab Team (University of Padova) trial run
More information:
For more information, please contact agile.production(a)metricsproject.eu