Icon--AD-black-48x48Icon--address-consumer-data-black-48x48Icon--appointment-black-48x48Icon--back-left-black-48x48Icon--calendar-black-48x48Icon--Checkbox-checkIcon--clock-black-48x48Icon--close-black-48x48Icon--compare-black-48x48Icon--confirmation-black-48x48Icon--dealer-details-black-48x48Icon--delete-black-48x48Icon--delivery-black-48x48Icon--down-black-48x48Icon--download-black-48x48Ic-OverlayAlertIcon--externallink-black-48x48Icon-Filledforward-right_adjustedIcon--grid-view-black-48x48Icon--info-i-black-48x48Icon--Less-minimize-black-48x48Icon-FilledIcon--List-Check-blackIcon--List-Cross-blackIcon--list-view-mobile-black-48x48Icon--list-view-black-48x48Icon--More-Maximize-black-48x48Icon--my-product-black-48x48Icon--newsletter-black-48x48Icon--payment-black-48x48Icon--print-black-48x48Icon--promotion-black-48x48Icon--registration-black-48x48Icon--Reset-black-48x48share-circle1Icon--share-black-48x48Icon--shopping-cart-black-48x48Icon--start-play-black-48x48Icon--store-locator-black-48x48Ic-OverlayAlertIcon--summary-black-48x48tumblrIcon-FilledvineIc-OverlayAlertwhishlist

Important Cookie Information

This website uses cookies for reasons of functionality, comfort, and statistics. You can change those settings at any time in the footer on "Privacy Settings".

Bosch Center for Artificial Intelligence

Research

Our Research Fields

We create differentiating AI solutions along with concrete lead applications, and ensure to transfer them into Bosch businesses.

AI-Based Dynamics Modeling

AI-Based Dynamics Modeling

Machine learning has been successfully applied on stationary physical systems. However, accurate modeling of dynamic systems is still a challenge. Our goal is to develop statistical, nonparametric and real-time capable dynamics models.

Rich and Explainable Deep Learning Perception

Rich and Explainable Deep Learning Perception

As a key enabler for autonomous driving, we strive to understand the behavior of deep neural networks for accurate and reliable perception.

Large Scale Deep Learning

Large-Scale Deep Learning

We are exploring techniques to scale algorithms and pipelines for large-scale, real-world data sets. Our focus lies on multi-dimensional hyper-parameter spaces as a key enabler across domains.

Environment Understanding and Decision Making

Environment Understanding and Decision Making

By making inference in probabilistic graphical model-based hierarchical environment models, we provide multi-modal behavior predictions of all agents in any given scene and determine how likely certain situations are to occur.

Control Optimization Through Reinforcement Learning

Control Optimization Through Reinforcement Learning

Automatic calibration and adaptation of controllers is central to the vision of a self-calibrating factory. We intend to exploit modeling knowledge and new exploration strategies for effective learning control.

Dynamic Multi-Agent Planning

Dynamic Multi-Agent Planning

Coordinating fleets of autonomous systems is complex. We develop dynamic planning techniques for optimal and safe operation of multi-agent robot systems in uncertain environment.