12 accepted papers
Distribution shifts between operational domains can severely affect the performance of learned models in self-driving vehicles (SDVs). While this is a well-established problem, prior work has mostly explored naive solutions such as fine-tuning, focusing on the motion prediction task. In this work, w
Visual observation of objects is essential for many robotic applications, such as object reconstruction and manipulation, navigation, and scene understanding. Machine learning algorithms constitute the state-of-the-art in many fields but require vast data sets, which are costly and time-intensive to
"Accurate 3D object detection is vital for automated driving. While lidar sensors are well suited for this task, they are expensive and have limitations in adverse weather conditions. 3+1D imaging radar sensors offer a cost-effective, robust alternative but face challenges due to their low resolutio…
This work uses game theory as a mathematical framework to address interaction modeling in multi-agent motion forecasting and control. Despite its interpretability, applying game theory to real-world robotics, like automated driving, faces challenges such as unknown game parameters. To tackle these,…
Offline reinforcement learning (RL) provides a framework for learning decision-making from offline data and therefore constitutes a promising approach for real-world applications such as automated driving (AD). Especially in safety-critical applications, interpretability and transferability are cruc
It is widely assumed that considering vehicle interactions for trajectory prediction can significantly improve accuracy. All environmental sensors of an automated vehicle (AV) suffer from occlusion. Therefore, relevant vehicles can be occluded by others, especially in dense traffic situations, and r
This letter presents automated driving using polygon clipping (A-D-PolyC), a novel framework for lane change behavior planning of automated vehicles on highways. It assumes that a mission planning layer generates lane change requests. In crowded traffic scenes, various variants for the lane change e
The spring loaded inverted pendulum (SLIP) model has been extensively shown to be fundamental for legged locomotion. However, the way this low-order template model dynamics is anchored in high-dimensional articulated multibody systems describing compliantly actuated robots (and animals) is not obvio
This paper presents a purely visual semantic mapping framework using omnidirectional images. The approach rests upon the robust segmentation of the robot's local free space, replacing conventional range sensors for the generation of occupancy grid maps. The perceptions are mapped into a bird's eye v…
This paper presents a novel generic formulation of Timed-Elastic-Bands for efficient online motion planning of car-like robots. The planning problem is defined in terms of a finite-dimensional and sparse optimization problem subject to the robots kinodynamic constraints and obstacle avoidance. Contr…
The work discusses two control concepts. Both approach oscillation damping for elastic link robotic arms from fundamentally different theoretical directions. Despite their principal difference, the work consolidates both control schemes by mathematically deriving the equivalence of the resulting con
Link elasticity is commonly understood to be a detrimental side-effect of imperfect mechanical designs of robotic arms and comparable machinery. In contrast to this notion, this paper demonstrates a novel approach to exploit intrinsic robot link compliance in order to estimate a priori unknown paylo…