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Autonomy for Mobility

The Robot Learning Lab organizes a bi-weekly reading group (no ECTS) on Autonomy for Mobility in cooperation with the Autonomous Intelligent Systems Lab. Here we discuss recent publications on the field as well as work in progress in our groups. The main focus of this reading group is the area of state estimation and perception for autonomous navigation scenarios. Speakers are the PhD students of the AIS and RL labs.

During the meeting, the presenter gives a short talk (25 min) summarizing a paper either previously voted for or their own research work and leads a subsequent discussion (30 min). The target audience consists of Professors, PostDocs, PhDs, and interested Master's students.

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Next Meeting:

  • Date: 13/05/2022, 3pm
  • Presenter: Dulce Adriana Gómez Rosal
  • Title: CalibDNN: Multimodal Sensor Calibration for Perception Using Deep Neural Networks
  • Abstract: Current perception systems often carry multimodal imagers and sensors such as 2D cameras and 3D LiDAR sensors. To fuse and utilize the data for downstream perception tasks, robust and accurate calibration of the multimodal sensor data is essential. We propose a novel deep learning-driven technique (CalibDNN) for accurate calibration among multimodal sensor, specifically LiDAR-Camera pairs. The key innovation of the proposed work is that it does not require any specific calibration targets or hardware assistants, and the entire processing is fully automatic with a single model and single iteration. Results comparison among different methods and extensive experiments on different datasets demonstrates the state-of-the-art performance.
  • Zoom Link

Paper Voting:

Please provide your vote regarding the paper to be presented during the subsequent meeting:


In case you would like to individually suggest a paper or topic to be presented: Suggestion Form

Future Dates:

Date Name (Lab) Paper / Title
03/06/22 Niklas Wetzel (AIS) TBA
01/07/22 Johan Vertens (AIS) TBA
29/07/22 Niclas Voedisch (AIS/RL) TBA

Past Dates:

Date Name (Lab) Paper / Title
11/03/22 Johannes Meyer Context-Aware Mixup for Domain Adaptive Semantic Segmentation
11/03/22 Daniele Cattaneo LCDNet: Deep Loop Closure Detection and Point Cloud Registration for LiDAR SLAM
01/02/22 Kshitij Sirohi EfficientLPS: Efficient Lidar Panoptic Segmentation incl. new insights
21/01/22 Christopher Lang Contrastive Object Detection Using Knowledge Graph Embeddings