In the period of industrial experience: 2013 – today.
Autonomous driving. German auto supplier Continental still may be best known as a producer of traditional auto parts such as tires and brakes, but it makes its intention to become a major player in autonomous vehicles. Over 1,300 specialists at Continental are working on advanced driver assistance systems and the foundations of automated driving. In around 15 years, engineers from Continental have worked on over 100 driver assistance projects for automakers around the world. Since 2007, Continental has been committed to research projects for automated driving.
Automated driving project is a cooperation between the automobile manufacturer BMW and the automotive supplier Continental. Both companies teamed up to develop self-driving car technology, or as they call it, an electronic co-pilot for cars (in German HAF – hochautomatisiertes Fahren). The main goal of the joint venture is to develop and test technologies that would usher in an era of highly automated driving on European freeways from 2020, with fully automated systems expected from 2025. [more]
In the period of academic research: 2008 – 2013.
IntellAct addresses the problem of understanding and exploiting the meaning (semantics) of manipulations in terms of objects,
actions and their consequences for reproducing human actions with machines. This is in particular required for the interaction between humans and robots in which the robot has to understand the human action and then to transfer it to its own embodiment. [more]
Xperience project will address this problem by structural bootstrapping, an idea taken from child language acquisition research. Structural bootstrapping is a method of building generative models, leveraging existing experience to predict unexplored action effects and to focus the hypothesis space for learning novel concepts. This developmental approach enables rapid generalization and acquisition of new knowledge and skills from little additional training data. [more]
GARNICS project aims at 3D sensing of plant growth and building perceptual representations for learning the links to actions of a robot gardener. Plants are complex, self-changing systems with increasing complexity over time. Actions performed at plants (like watering), will have strongly delayed effects. Thus, monitoring and controlling plants is a difficult perception-action problem requiring advanced predictive cognitive properties, which so far can only be provided by experienced human gardeners. [more][video 1][video 2]
PACO-PLUS brings together an interdisciplinary research team to design and build cognitive robots capable of developing perceptual, behavioural and cognitive categories that can be used, communicated and shared with other humans and artificial agents. To demonstrate our approach we are building robot systems that will display increasingly advanced cognitive capabilities over the course of the programme. They will learn to operate in the real world and to interact and communicate with humans. [more]