This workshop focuses on the unique perceptual problems related to autonomous navigation in indoor and outdoor human environments. These problems include human detection and tracking from 2D and/or 3D data, human posture detection and prediction, object detection, segmentation, trajectory forecasting and any other perceptual task that, when solved, provides valuable information to autonomous agents and robots that need to navigate safely in human crowded environments.
Last years the community has paid increasing attention to these perceptual problems and has provided annotated datasets to learn to solve them and evaluate them, yet restricted to the point of view of autonomous vehicles. Robots and other navigating agents, however, view the world from a different perspective, can go indoors, get closer to humans and need to perceive other types of information. In this workshop, we present the JackRabbot social navigation dataset , a novel annotated dataset with the signals from our mobile manipulator JackRabbot. For the workshop we launch the first set of visual challenges, to benchmark perceptual algorithms in this new type of data.
The dataset contains 67 minutes of ground truth annotated sensor data acquired from the JackRabbot mobile manipulator and includes more than 50 indoor and outdoor sequences in a university campus environment. Sensor data includes a stereo RGB 360° cylindrical video stream, 3D point clouds from two LiDAR sensors, audio and GPS positions.
In the workshop we will present the winners of the first challenge. We have also as invited speakers world renowned expers in perception for autonomous navigation. We aim to foster discussion between the attendants to find useful synergies and applications of the solutions of perceptual tasks for navigation in human environments.
In this first phase, the annotations of the JackRobot Dataset include:
We invite researchers to submit their papers addressing topics related to autonomous (robot) navigation in human environments. Relevant topics include:
Submisison format should match the ICCV format, e.g. 8 pages, double column format. By submitting to this workshop, authors agree to the review process and understand that we will do our best to match papers to the best possible reviewers. The reviewing process is double blind. Submission to the challenge is independent from the paper submission, but we encourage paper authors to submit to one of the challenges.