This workshop brings together researchers from robotics, computer vision, and machine learning to examine challenges and opportunities emerging at the boundary between spatial perception and high-level task execution. Recent years have seen a growing interest towards metric-semantic understanding, which consists in building a semantically annotated (or object-oriented) model of the environment. This is pushing researchers from traditional research on SLAM towards more advanced forms of spatial perception. On the other hand, researchers have been looking at high-level task execution using modern tools from reinforcement learning and traditional decision making. The combination of these research efforts in perception and task execution has the potential to enable applications such as visual question answering, object search and retrieval, and are providing more intuitive ways to interact with the user. This workshop creates an exchange opportunity to connect researchers working in metric-semantic perception and high-level task execution. In particular, the workshop will bring forward the latest breakthroughs and cutting-edge research on spatial perception and high-level task execution. Besides the usual mix of invited talks and poster presentations, the workshop involves two interactive activities. First, we will provide a hands-on tutorial on a state-of-the-art library for metric-semantic reconstruction, which can be useful to both researchers and practitioners. Second, we will organize the GOSEEK challenge (details to follow), in conjunction with the release of a photo-realistic Unity-based simulator, where participants will need to combine perception and high-level decision making to find an object in a complex indoor environment.
|08:45-09:00||Registration, welcome, and competition overview||-|
|09:00-09:30||Invited talk||Leslie Kaelbling (MIT)|
|10:30-11:00||Invited talk||Raia Hadsell (DeepMind)|
|11:30-12:00||Invited talk||Dhruv Batra (Georgia Tech)|
|12:00-12:30||Invited talk||Sertac Karaman (MIT)|
|1:30-2:00||Invited talk||Andrew Davison (Imperial College)|
|2:00-2:30||Invited talk||Cesar Cadena (ETH Zurich)|
|2:30-3:00||Hands-on Tutorial: Metric-Semantic Mapping||-|
|3:00-3:30||Coffee break & poster session||-|
|3:30-4:00||Invited talk||Marco Pavone (Stanford)|
|4:00-4:30||Invited talk||Davide Scaramuzza (UZurich)|
|4:30-5:00||Keynote presentation: competition winner||-|
|5:00-5:30||Panel discussion and concluding remarks||-|
We are organizing the GOSEEK competition, where participants create an RL agent that combines perception and high-level decision-making to search for objects placed within complex indoor environments from a Unity-based simulator. Simply put: like PACMAN, but in a realistic scene and with realistic perception capabilities. Several data modalities will be provided from both the simulator ground truth and a perception pipeline (e.g., images, depth, agent location) to enable the participants to focus on the RL/search aspects. The contest will be hosted on the EvalAI platform, where participants will submit solutions, via docker containers run on AWS instances, for scoring. The winner of the competition will receive a monetary prize and will give a keynote presentation at the workshop.
To get updates about the challenge, please send an email to “email@example.com” with subject “GOSEEK: subscribe” and we will add you to our Goseek-Challenge@mit.edu mailing list!
Submission link: https://easychair.org/conferences/?conf=pal2020icraworkshop
Participants are invited to submit an extended abstract or short papers (up to 4 pages in ICRA format) focusing on novel advances in spatial perception, reinforcement learning, and at the boundary between these research areas. Topics of interest include but are not limited to: