CVinHRC workshop will be held virtually, as ICCV 2021

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CVinHRC | ICCV 2021 – International Conference on Computer Vision

Topics Covered

The technological breakthrough in robotics and the needs of the factories of future (Industry 4.0) bring the robots out of their cages to work in close collaboration with humans, aiming to increase productivity, flexibility and autonomy in production. To enable true and effective human-robot collaboration, the perception system of such collaborative robots should be endorsed with advanced computer vision methods that will transform them into active and effective co-workers.

Recent advances in the field of computer vision are anticipated to resolve several complex tasks that require human-robot collaboration in manufacturing and logistics domains. However, the applicability of existing computer vision techniques in such factories of the future is hindered from the challenges that real, unconstrained industrial environments with cobots impose, such as variability in position and orientation of manipulated objects, deformation and articulation, existence of occlusions, motion, dynamic environments, human presence and more.

In particular, the variability of manufactured parts and the lighting conditions in realistic environments renders robust object recognition and pose estimation challenging, especially when collaborative tasks demand dexterous and delicate grasping of objects. Deep learning can further advance the existing methods to cope with occlusions and other incurred challenges, while also the combination of learning with visual attentional models could reduce the need for data redundancy by selecting most prominent and rich-in-context viewpoints to be memorized, boosting the overall performance of the vision systems. Moreover, close distance collaboration with humans requires accurate SLAM and real time monitoring and modelling of the human body to be applied for robot manipulation and AGV navigation tasks in unconstrained environments, ensuring safety and human faith to the new automation solutions. Alongside, further advanced semantic SLAM methods are needed to endorse cobots with robust long-term autonomy with no or minimal human intervention. What is more, the fusion of deep learning with multimodal perception can offer solutions to complex manufacturing tasks that require powerful vision systems to deal with challenges such as articulated objects and deformable materials handled by the robots. This can be achieved not only by using vision systems as passive observers of the scene, but also with the active involvement of the collaborative robots endorsed with visual searching and view planning capabilities to drastically increase their knowledge for their surroundings.

The goal of this workshop is to bring together researchers from academia and industry in the field of computer vision and enable them to present novel methods and approaches that set the basis for further advanced robotic perception dealing with the significant challenges of human robot collaboration in the factories of future.

We encourage submissions of original and unpublished works that address computer vision for robotic applications in manufacturing and logistics domain, including but not limited to the following:

  • Deep learning for object recognition and pose estimation in manufacturing and logistics
  • 6-DoF object pose estimation for grasping
  • Real time object tracking and visual servoing
  • Vision-based object affordances learning
  • Vision-based manipulation skills modelling and knowledge transfer
  • View planning with robot active vision
  • Human presence modelling, detection and tracking in real factory environments
  • Human-robot workspace modelling for safe manipulation
  • Semantic SLAM and lifelong environment learning
  • Safe AGV navigation based on visual input
  • Multi-AGVs perception and coordination for multiple tasks
  • Visual search for AGVs and manipulators in industrial environments
  • Sensor fusion (Camera, Lidar, Haptic, etc.) for enhanced scene understanding
  • Vision-based attention modeling for collaborative tasks

Invited Speakers :

HR-Recycler participation in “Industrial Human Robot Collaboration” projects cluster

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HR-Recycler participated in a Workshop on the Cluster of “Industrial Human Robot Collaboration” projects that took place in Brussels, on 1st July 2019.

The workshop was organized by the European Commission (Bram Vanderborght, Andrea Ceglia, Laszlo Hetey and Jurgen Tiedje) and its aim was to prepare a publicly available policy report illustrating the potential benefits of funding research and innovation on robotics, identify emerging technology trends, environmental, economic and societal impacts. This report will be presented at European Research and Innovation Days in Brussels, from 24 to 26 September 2019 (

The following projects of the Cluster of “Industrial Human Robot Collaboration” participated:

The workshop started with a short presentation of each project of the Cluster, presented by each project’s representative. Each presentation included the motivation, main goal and objectives of the project, the consortium and a brief description of the proposed technical solution and the related Use Cases.

The next part of the workshop included the Technological Analysis. More specifically, the current Technology Readiness Levels (TRL) achieved by the current research projects in this area were analysed and the challenges for high TRL levels were discussed. Regarding integration/implementation issues the following aspects were discussed: Standards (if sufficiently developed and translated in good practices), Certification (how it is done, if it can be done for a wide range of applications, etc.), Interoperability (how it is implemented), Benchmarking and Reproducibility of scientific research.

Another interesting point of discussion was the industrial and economic impact, where several issues were analysed. New business models arise when moving from traditional industrial robots to collaborative robots, while the economic viability of investing in robots that collaborate with human workers has been extensively studied. Other issues include the targeted increase of productivity (e.g. time, quality, resources, working conditions), barriers to valorization, the potential challenges for startups, targeting liability and intellectual property. Finally, the role of Digital Innovation Hubs was discussed.

Last but not least, the Social Impact by moving from traditional industrial robots to collaborative robots was discussed. It is of high importance to ensure that the use of Human-Robot Collaboration in industry is able to improve working conditions and increase the amount of jobs. Ethical aspects were also discussed (ethics screening, job loss, handling of privacy, position of women).

The importance of EU collaborative projects was stressed, as well as potential improvements on how subsequent public or private investments can put in place the technologies that result from these projects.

The importance of EU collaborative projects was stressed, as well as potential improvements on how subsequent public or private investments can put in place the technologies that result from these projects.

What is also important is to place the initiative more at end-user companies that have specific needs, instead of EU research centers.