<html><head><meta http-equiv="Content-Type" content="text/html charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">CALL FOR PAPERS:</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">ICRA 19 Workshop on Algorithms and Architectures for Learning-in-the-Loop Systems in Autonomous Flight</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">Montreal, Canada</span></div><br class=""><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">WEBPAGE:</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><a href="https://uav-learning-icra.github.io/2019/" class="" style="text-decoration: none;"><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(17, 85, 204); font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: underline; -webkit-text-decoration-skip: none; vertical-align: baseline; white-space: pre-wrap;">https://uav-learning-icra.github.io/2019/</span></a></div><br class=""><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">DATES:</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">Paper submission deadline: 7-Apr-2019, 11:59PM AoE</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">Author notification: 29-Apr-2019</span></div><br class=""><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">SUBMISSION INFORMATION:</span></div><p dir="ltr" class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 12pt; background-color: rgb(255, 255, 255);"><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(36, 41, 46); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">Submission link: </span><a href="https://easychair.org/my/conference.cgi?conf=lsaf19" class="" style="text-decoration: none;"><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(3, 102, 214); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: underline; -webkit-text-decoration-skip: none; vertical-align: baseline; white-space: pre-wrap;">https://easychair.org/my/conference.cgi?conf=lsaf19</span><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;"><br class=""></span></a><span class="" style="font-size: 9pt; font-family: Arial; background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">Detailed submission instructions: </span><a href="https://uav-learning-icra.github.io/2019/" class="" style="text-decoration: none;"><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(17, 85, 204); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; text-decoration: underline; -webkit-text-decoration-skip: none; vertical-align: baseline; white-space: pre-wrap;">https://uav-learning-icra.github.io/2019/</span><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(36, 41, 46); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;"><br class=""></span></a><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(36, 41, 46); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">Questions can be directed to: </span><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(3, 102, 214); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="mailto:lsaf19@easychair.org" class="">lsaf19@easychair.org</a></span></p><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">OVERVIEW:</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">In past years, model-based techniques have successfully endowed aerial robots with impressive capabilities like high-speed navigation through unknown environments. However, task specifications, like goal positions, are often still hand-engineered. Machine learning and deep learning have emerged as promising tools for higher-level autonomy, but are more difficult to analyze and implement in real-time. Furthermore, maintaining high thrust-to-weight ratios for agility directly contradicts the need to carry sensor and computation resources, making hardware and software architecture equally crucial decisions.</span></div><br class=""><p dir="ltr" class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 12pt; background-color: rgb(255, 255, 255);"><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(36, 41, 46); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">This workshop aims to bring together researchers in the complementary fields of aerial robotics, learning, and systems to discuss the following themes:</span><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(36, 41, 46); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;"><br class=""></span><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(36, 41, 46); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- Learning for autonomous robots - How should learning be incorporated into robots' perception-action loops?</span><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(36, 41, 46); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;"><br class=""></span><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(36, 41, 46); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- Structure in learning - How can models, structure, and priors enhance learning on robots?</span><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(36, 41, 46); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;"><br class=""></span><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(36, 41, 46); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- Performance guarantees - How can we analyze closed-loop performance of learning-in-the-loop systems</span><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(36, 41, 46); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;"><br class=""></span><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(36, 41, 46); background-color: transparent; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- Software+hardware co-design - How can we implement learning algorithms on resource-constrained UAVs? How should we simultaneously optimize algorithms and hardware choices to create lightweight, but highly-capable, UAVs?</span></p><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">SUBMISSION INFORMATION:</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">We are soliciting 4-page papers (not including references) with up to a 2-minute accompanying video. </span><span class="" style="font-size: 9pt; font-family: Arial; color: rgb(36, 41, 46); font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">We welcome work with experimental validation (including initial preliminary results) or addressing challenges associated with real-world implementation. We also welcome simulation-only papers that convincingly address why the utilized simulator is a compelling representation of real-world conditions and papers with validation on other robotics platforms that could be applied to UAVs. We especially encourage papers that share valuable “failure analyses" or “lessons learned" that would benefit the community. We welcome work at all stages of research, including work-in-progress and recently accepted or published results.</span></div><br class=""><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">SCOPE AND TOPICS:</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">Topics of interest include (but are not limited to):</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- Combining model-based and model-free methods for autonomous robotics</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- Online learning and adaptation in mapping, perception, planning, and/or control for UAVs</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- End-to-end learning of perception-action loops for flight</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- Sample efficient learning on flying robots</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- Learning for high-level autonomy in applications such as (but not limited to) disaster response, cinematography, search and rescue, environmental monitoring, aerial manipulation, agriculture, and inspection</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- Closed-loop analysis learning-in-the-loop systems</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- Metrics for evaluating the benefits of incorporating learning into perception-action loops or</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">incorporating models into learning algorithms</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- Challenges implementing learning algorithms in real-time on sensorimotor systems</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- Novel architectures that use multi-agent networks or the cloud to decentralize demanding computations</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">- Insights into architecture design, system component choice, and implementation details (including “failed designs") of real-time learning-in-the-loop algorithms</span></div><br class=""><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">ORGANIZERS:</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">Dr. Aleksandra Faust, Google Brain</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">Dr. Vijay Janapa Reddi, Harvard University</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">Dr. Angela Schoellig, University of Toronto</span></div><div class="" style="line-height: 1.656; margin-top: 0pt; margin-bottom: 0pt;"><span class="" style="font-size: 9pt; font-family: Arial; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; vertical-align: baseline; white-space: pre-wrap;">Dr. Sarah Tang, University of Pennsylvania/Nuro, Inc.</span></div></body></html>