Learning Object Placements from VR with GMMs

In the bachelor thesis Robots learning geometric groundings of object arrangements for household tasks from virtual reality demonstrations Thomas Lipps implemented a method to learn object placements in a kitchen environment. First, he acquired a data set by performing table setting scenarios in the virtual kitchen by using VR and a pipeline created in previous works from Andrei Haidu und Alina Hawkin.

These data samples were then inputted in the ROS python package costmap_learning. This package takes the object positions and orientations of the used objects in VR and encodes these separated in Gaussian Mixture Models (GMM). The software architecture allows to learn separated object placements for different kitchen environments, tables, context, humans and obviously object types.

Lastly, the package only returns relevant and non redundant knowledge. The former is achieved by identifying possible relations between the object which should be placed and already placed objects. The latter is reached by filtering the result with the already placed objects. This behavior is visualized in a table setting scenario in the given video. The ROS Interface in CRAM is implemented in the CRAM package cram_learning_vr.

2020/10/19 11:34 · tlipps

CRAM @ ICRA 2020

This summer our paper on CRAM plan transformations titled “Towards Plan Transformations for Real-World Mobile Fetch and Place” has been presented at the ICRA 2020 conference in a virtual form. You can see the video of the presentation here.

You can read more about plan transformations at the EASE blog or look at the implementation in the cram_plan_transformation package.

2020/08/24 16:05 · gkazhoya

PyCRAM with PyBullet

For the Bachelor Thesis of Andy and Dustin Augsten and later Jonas Dech CRAM was newly implemented in Python. The purpose behind this decision was to make the concepts of CRAM easier accessible to a wider audience.

Currently PyCRAM doesn't include all features of CRAM but the core features are implemented for example the CRAM Plan Language, Process Modules, Motion Designator, the BulletWorld and it's reasoning. While a lot of features, that are already in CRAM, aren't yet implemented in PyCRAM, it is already possible to write a functioning plan for a robot (see the second demo here). With the BulletWorld it is also possible to simulate these plans for testing or to plan future actions. The reasoning mechanisms of the BulletWorld allow to get information about the relationship of two objects in the BulletWorld.

Currently the CRAM Team also works to implement new features for PyCRAM, so stay tuned for more updates.

Below you can see a video which highlights the current capabilities of the PyCRAM framework.

2020/07/30 10:43 · jdech

RoboCup@Home German Open 2019

The CRAM Team participated at the German league of RoboCup@Home 2019! Within the Master Project Suturo we had a team of five Master's students, three of whom worked with CRAM on the HSR robot. We are happy to announce that CRAM as a framework was the cornerstone to solve the robot tasks. We used CRAM to write general plans, so the robot managed to enter the arena on its own and perform pick and place tasks. Of course we have cooperated with other frameworks that come from the Institute for AI of the University of Bremen, which we are affiliated with.

Participating in a RoboCup was an exciting and rewarding experience for all of us. Furthermore it showed the students just once again why it is so important to incorporate Failure Handling and test their system for all eventualities. We look forward to the future and hope for a second time CRAM@Robocup.

2019/06/12 11:31 · vanessa

CRAM Logo is out

There was a process in which this logo was created. At first it was too detailed or even stuffed. Actually, a CRAM logo needs everything, a camera, some tires, a lot of grippers and much more (because CRAM can do so much).

However, we had to reduce it so far that it is abstract but still recognizable. Therefore, we are very satisfied with the logo: it should represent the manipulation of itself and the environment at the same time. We hope you enjoy it too!

2019/02/05 15:27 · vanessa

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