[robotics-worldwide] [meetings] CfP RSS Workshop on Perception and Control for Fast and Agile Super-Vehicles

Varun Murali mvarun at mit.edu
Wed Mar 11 17:45:43 PDT 2020


Please find below the call for papers to the RSS’20 Workshop titled
“Perception and Control for Fast and Agile Super-Vehicles” to be held on
the 12th of July at Oregon State University at Corvallis, Oregon.



Workshop website: https://urldefense.com/v3/__https://mit-fast.github.io/WorkshopRSS20SuperVehicles/__;!!LIr3w8kk_Xxm!8j1gmOfWXZt8dAXy3K8yqWJtawtBczxAkCMt_STryKA3r7AXJmFbePLuHQY5T_FR-WaryzoU$ 



We invite 2-page extended abstract submissions for original work in
perception and control for high speed navigation and topics of interest to
this workshop. Topics of interest to this workshop are (but not limited to):

   -

   Drone racing
   -

   High speed localization and mapping
   -

   Perception aware control and planning
   -

   Trajectory optimization for aggressive flight
   -

   Robust control for high speed flight
   -

   Accurate simulation of highly agile and fast aerial vehicles



 Authors will have the opportunity to participate in a poster session at
the workshop.



** Important dates:

Abstract submission deadline: April 9th 2020

Acceptance Notification: April 16th 2020

Workshop date: July 12th 2020



Please email all submissions to super-vehicles-rss20-submit at mit.edu with
‘RSS20 Super Vehicles’ in the subject line.



** Abstract for the workshop

As autonomous aerial vehicles not only become more robust and capable, but
also are slowly being adopted in many industrial tasks, a novel branch of
autonomy has recently caught the interest of many researchers: autonomous
drone racing. Not only does it combine the difficulties in perception,
estimation, planning, control, and their intersections, but it also tests
their ability to perform under harsh, real-world conditions.

Expert human pilots have demonstrated an astonishing level of control,
racing remotely controlled drones at their physical limits, and inspiring
roboticists to push the algorithmic limits to a human-competitive level. As
advances in algorithmic perception and control for fast and agile robotic
vehicles materialize, autonomous racing vehicles are quickly approaching
the ability to contend against human pilots in head to head races. Most
recently, Lockheed Martin, NVIDIA and the Drone Racing League (DRL)
successfully organised the first season of the AlphaPilot program (
https://urldefense.com/v3/__https://www.herox.com/alphapilot__;!!LIr3w8kk_Xxm!8j1gmOfWXZt8dAXy3K8yqWJtawtBczxAkCMt_STryKA3r7AXJmFbePLuHQY5T_FR-R-llK0p$ ) and the AIRR drone racing challenge (
https://urldefense.com/v3/__https://thedroneracingleague.com/airr/__;!!LIr3w8kk_Xxm!8j1gmOfWXZt8dAXy3K8yqWJtawtBczxAkCMt_STryKA3r7AXJmFbePLuHQY5T_FR-dnL-oRs$ ), where multiple teams have
successfully deployed and raced their autonomy algorithms against each
other. These advances may ultimately lead to autonomous super-vehicles,
i.e., next-generation autonomous robots that are capable of achieving
super-human maneuvering and racing capabilities. The resulting algorithms
may become invaluable components of high-throughput autonomy software,
e.g., to maneuver cars out of traffic accidents. However, the development
of these super-vehicles brings significant challenges. While perceiving the
environment at high speeds with low latency has been investigated
throughout the last decade, many open research questions still remain. On
the other side, time-optimal planning with well known or learned dynamic
and aerodynamic models could give autonomous drones an advantage over human
pilots, or let them learn from each other. The purpose of this workshop is
to identify gaps in current techniques, and discuss possible solutions to
the remaining and newly uncovered research questions.. Is end to end deep
learning a viable option to solve these high speed interactions? What can
we model, what can we learn, and could we combine these techniques to
achieve superhuman capabilities? What are the transfer gaps between
simulation, learning and real world systems, and how can we bridge them to
achieve truly superior autonomous mobile robots?


** Attendance Notes for RSS

For each accepted paper/poster, one author is required to register for the
RSS workshops to present the contribution. IMPORTANT: If your
paper/poster’s representative is from a country that requires a visa to
enter the United States, the RSS organizers are able to provide a visa
support letter. If you require such a letter, **please confirm the full
name and country of citizenship of the representative before April 23rd,
2020**. Due to expected long visa processing times in the US, we urge you
to start the visa application process as soon as possible. Please note that
the RSS organizers are only able to provide one such support letter per
contribution.

Organizers:

Varun Murali, MIT

Phillip Foehn, UZH

Prof. Davide Scaramuzza, UZH

Prof. Sertac Karaman, MIT


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