<div dir="ltr"><div dir="ltr"><div class="gmail_default" style="font-size:small"><div><div><p style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>When:</b> </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit"> Friday, February 12th at<b> 11:10 am CT</b></font></font><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b> </font></font><font color="#000000">Zoom Virtual Talk (</font><b><font color="#0000ff"><a href="https://uchicagogroup.zoom.us/webinar/register/WN_AtjkUtMlQxSS5wkgA19iuA" target="_blank">register in advance here</a></font></b><font color="#000000">)</font></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b> </font></font></font>Ian Abraham, Carnegie Mellon University</p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><span style="color:rgb(0,0,0)"><br></span></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><span style="color:rgb(0,0,0)"><br></span></font></p></div></div><div><b>Title:</b> Runtime Active Learning for Reactive Robotics<br><br><b>Abstract:</b> Robotic systems rely on human engineered guidance, programming of tasks, and oracle information that enable them to operate in our world. What happens to robotic systems when we are unable to perform as an oracle, creating an absence of information about what is known and unknown to a robot? Can we expect robotic systems to be intentional about how they seek out information necessary to operate? And what are the necessary requirements for them to explore and navigate the complexities that they will face as we make them operate in increasingly unstructured environments?<br><br></div><div>In this talk, I argue that having the ability to actively acquire and seek out informative data that improve robot learning is a stepping stone towards autonomy detached from human engineers. Using existing methods and tools from hybrid control theory, I first create the theoretical groundwork for improving the learning capabilities of robots by combining various modes of learning subject to robot dynamics and stability constraints. The problem of active learning through experimental design, where anticipated sensor data is optimized, motivates the use of methods from ergodicity and ergodic exploration that enable robots to sample and sense from multiple information sources while simultaneously ensuring that the robot does not ignore unexplored parts of an environment. I illustrate the use of ergodicity as a promising approach for learning models in complex and spatially sparse environments using only rudimentary contact sensing. These results are extended to more general active learning in dynamic state-spaces where robot safety and the quality of informative measurements are balanced using hybrid control theoretic analysis and known stabilizing controllers. Last, I argue that we should not only care about active learning, but also how we model and represent the dynamics of robotic systems. The class of infinite linear embeddings is presented as a candidate model that simplifies and improves the control and active learning capabilities of robotic systems. Through simulated and experimental application, I illustrate the potential of the presented approaches for pushing the boundaries of robotic systems towards being more capable, self-sufficient, and curious systems that intentionally seek out the unknown and complex nature of interacting in our world.<br></div><div><br></div><div><b>Bio:</b> Ian Abraham is a Postdoctoral scholar at the Robotics Institute at Carnegie Mellon University. He received the B.S. degree in Mechanical and Aerospace Engineering from Rutgers University and the M.S. and Ph.D degree in Mechanical Engineering from Northwestern University at the Center for Robotics and Biosystems. His Ph.D. work focuses on developing formal methods for robot sensing and runtime active learning. During his Ph.D. he interned at the NVIDIA Seattle Robotics Lab where he worked on robust model-based control for large parameter uncertainty. He also participated in the DARPA OFFSET FX-3 Urban Swarm Challenge and is the recipient of the 2019 King-Sun Fu IEEE Transactions on Robotics Best Paper award.</div><div><br></div><div><br></div><div><br></div><div><b>Host:</b> <a href="mailto:mwalter@ttic.edu" target="_blank">Matthew Walter</a></div><div><br style="color:rgb(80,0,80)"></div><div><br></div><div><br></div><div><br></div></div><div><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><font face="arial, helvetica, sans-serif">Mary C. Marre</font><div><font face="arial, helvetica, sans-serif">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">6045 S. Kenwood Avenue</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Room 517</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL 60637</font></i></div><div><i><font face="arial, helvetica, sans-serif">p:(773) 834-1757</font></i></div><div><i><font face="arial, helvetica, sans-serif">f: (773) 357-6970</font></i></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Fri, Feb 12, 2021 at 10:00 AM Mary Marre <<a href="mailto:mmarre@ttic.edu">mmarre@ttic.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div dir="ltr"><div style="font-size:small"><div><div><p style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>When:</b> </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit"> Friday, February 12th at<b> 11:10 am CT</b></font></font><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b> </font></font><font color="#000000">Zoom Virtual Talk (</font><b><font color="#0000ff"><a href="https://uchicagogroup.zoom.us/webinar/register/WN_AtjkUtMlQxSS5wkgA19iuA" target="_blank">register in advance here</a></font></b><font color="#000000">)</font></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b> </font></font></font>Ian Abraham, Carnegie Mellon University</p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><span style="color:rgb(0,0,0)"><br></span></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><span style="color:rgb(0,0,0)"><br></span></font></p></div></div><div><b>Title:</b> Runtime Active Learning for Reactive Robotics<br><br><b>Abstract:</b> Robotic systems rely on human engineered guidance, programming of tasks, and oracle information that enable them to operate in our world. What happens to robotic systems when we are unable to perform as an oracle, creating an absence of information about what is known and unknown to a robot? Can we expect robotic systems to be intentional about how they seek out information necessary to operate? And what are the necessary requirements for them to explore and navigate the complexities that they will face as we make them operate in increasingly unstructured environments?<br><br></div><div>In this talk, I argue that having the ability to actively acquire and seek out informative data that improve robot learning is a stepping stone towards autonomy detached from human engineers. Using existing methods and tools from hybrid control theory, I first create the theoretical groundwork for improving the learning capabilities of robots by combining various modes of learning subject to robot dynamics and stability constraints. The problem of active learning through experimental design, where anticipated sensor data is optimized, motivates the use of methods from ergodicity and ergodic exploration that enable robots to sample and sense from multiple information sources while simultaneously ensuring that the robot does not ignore unexplored parts of an environment. I illustrate the use of ergodicity as a promising approach for learning models in complex and spatially sparse environments using only rudimentary contact sensing. These results are extended to more general active learning in dynamic state-spaces where robot safety and the quality of informative measurements are balanced using hybrid control theoretic analysis and known stabilizing controllers. Last, I argue that we should not only care about active learning, but also how we model and represent the dynamics of robotic systems. The class of infinite linear embeddings is presented as a candidate model that simplifies and improves the control and active learning capabilities of robotic systems. Through simulated and experimental application, I illustrate the potential of the presented approaches for pushing the boundaries of robotic systems towards being more capable, self-sufficient, and curious systems that intentionally seek out the unknown and complex nature of interacting in our world.<br></div><div><br></div><div><b>Bio:</b> Ian Abraham is a Postdoctoral scholar at the Robotics Institute at Carnegie Mellon University. He received the B.S. degree in Mechanical and Aerospace Engineering from Rutgers University and the M.S. and Ph.D degree in Mechanical Engineering from Northwestern University at the Center for Robotics and Biosystems. His Ph.D. work focuses on developing formal methods for robot sensing and runtime active learning. During his Ph.D. he interned at the NVIDIA Seattle Robotics Lab where he worked on robust model-based control for large parameter uncertainty. He also participated in the DARPA OFFSET FX-3 Urban Swarm Challenge and is the recipient of the 2019 King-Sun Fu IEEE Transactions on Robotics Best Paper award.</div><div><br></div><div><br></div><div><br></div><div><b>Host:</b> <a href="mailto:mwalter@ttic.edu" target="_blank">Matthew Walter</a></div><div><br></div><div><br></div></div><div><div dir="ltr"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><font face="arial, helvetica, sans-serif">Mary C. Marre</font><div><font face="arial, helvetica, sans-serif">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">6045 S. Kenwood Avenue</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Room 517</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL 60637</font></i></div><div><i><font face="arial, helvetica, sans-serif">p:(773) 834-1757</font></i></div><div><i><font face="arial, helvetica, sans-serif">f: (773) 357-6970</font></i></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Thu, Feb 11, 2021 at 5:46 PM Mary Marre <<a href="mailto:mmarre@ttic.edu" target="_blank">mmarre@ttic.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div dir="ltr"><div style="font-size:small"><div><div><p style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>When:</b> </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit"> Friday, February 12th at<b> 11:10 am CT</b></font></font><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b> </font></font><font color="#000000">Zoom Virtual Talk (</font><b><font color="#0000ff"><a href="https://uchicagogroup.zoom.us/webinar/register/WN_AtjkUtMlQxSS5wkgA19iuA" target="_blank">register in advance here</a></font></b><font color="#000000">)</font></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b> </font></font></font>Ian Abraham, Carnegie Mellon University</p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><span style="color:rgb(0,0,0)"><br></span></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><span style="color:rgb(0,0,0)"><br></span></font></p></div></div><div><b>Title:</b> Runtime Active Learning for Reactive Robotics<br><br><b>Abstract:</b> Robotic systems rely on human engineered guidance, programming of tasks, and oracle information that enable them to operate in our world. What happens to robotic systems when we are unable to perform as an oracle, creating an absence of information about what is known and unknown to a robot? Can we expect robotic systems to be intentional about how they seek out information necessary to operate? And what are the necessary requirements for them to explore and navigate the complexities that they will face as we make them operate in increasingly unstructured environments?<br><br></div><div>In this talk, I argue that having the ability to actively acquire and seek out informative data that improve robot learning is a stepping stone towards autonomy detached from human engineers. Using existing methods and tools from hybrid control theory, I first create the theoretical groundwork for improving the learning capabilities of robots by combining various modes of learning subject to robot dynamics and stability constraints. The problem of active learning through experimental design, where anticipated sensor data is optimized, motivates the use of methods from ergodicity and ergodic exploration that enable robots to sample and sense from multiple information sources while simultaneously ensuring that the robot does not ignore unexplored parts of an environment. I illustrate the use of ergodicity as a promising approach for learning models in complex and spatially sparse environments using only rudimentary contact sensing. These results are extended to more general active learning in dynamic state-spaces where robot safety and the quality of informative measurements are balanced using hybrid control theoretic analysis and known stabilizing controllers. Last, I argue that we should not only care about active learning, but also how we model and represent the dynamics of robotic systems. The class of infinite linear embeddings is presented as a candidate model that simplifies and improves the control and active learning capabilities of robotic systems. Through simulated and experimental application, I illustrate the potential of the presented approaches for pushing the boundaries of robotic systems towards being more capable, self-sufficient, and curious systems that intentionally seek out the unknown and complex nature of interacting in our world.<br></div><div><br></div><div><b>Bio:</b> Ian Abraham is a Postdoctoral scholar at the Robotics Institute at Carnegie Mellon University. He received the B.S. degree in Mechanical and Aerospace Engineering from Rutgers University and the M.S. and Ph.D degree in Mechanical Engineering from Northwestern University at the Center for Robotics and Biosystems. His Ph.D. work focuses on developing formal methods for robot sensing and runtime active learning. During his Ph.D. he interned at the NVIDIA Seattle Robotics Lab where he worked on robust model-based control for large parameter uncertainty. He also participated in the DARPA OFFSET FX-3 Urban Swarm Challenge and is the recipient of the 2019 King-Sun Fu IEEE Transactions on Robotics Best Paper award.</div><div><br></div><div><br></div><div><br></div><div><b>Host:</b> <a href="mailto:mwalter@ttic.edu" target="_blank">Matthew Walter</a></div><div><br></div><div><br></div><div><br></div></div><div><div dir="ltr"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><font face="arial, helvetica, sans-serif">Mary C. Marre</font><div><font face="arial, helvetica, sans-serif">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">6045 S. Kenwood Avenue</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Room 517</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL 60637</font></i></div><div><i><font face="arial, helvetica, sans-serif">p:(773) 834-1757</font></i></div><div><i><font face="arial, helvetica, sans-serif">f: (773) 357-6970</font></i></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Sun, Feb 7, 2021 at 11:14 AM Mary Marre <<a href="mailto:mmarre@ttic.edu" target="_blank">mmarre@ttic.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div style="font-size:small"><div><div><p style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>When:</b> </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit"> Friday, February 12th at<b> 11:10 am CT</b></font></font><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b> </font></font><font color="#000000">Zoom Virtual Talk (</font><b><font color="#0000ff"><a href="https://uchicagogroup.zoom.us/webinar/register/WN_AtjkUtMlQxSS5wkgA19iuA" target="_blank">register in advance here</a></font></b><font color="#000000">)</font></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b> </font></font></font>Ian Abraham, Carnegie Mellon University</p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><span style="color:rgb(0,0,0)"><br></span></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><span style="color:rgb(0,0,0)"><br></span></font></p></div></div><div><b>Title:</b> Runtime Active Learning for Reactive Robotics<br><br><b>Abstract:</b> Robotic systems rely on human engineered guidance, programming of tasks, and oracle information that enable them to operate in our world. What happens to robotic systems when we are unable to perform as an oracle, creating an absence of information about what is known and unknown to a robot? Can we expect robotic systems to be intentional about how they seek out information necessary to operate? And what are the necessary requirements for them to explore and navigate the complexities that they will face as we make them operate in increasingly unstructured environments?<br><br></div><div>In this talk, I argue that having the ability to actively acquire and seek out informative data that improve robot learning is a stepping stone towards autonomy detached from human engineers. Using existing methods and tools from hybrid control theory, I first create the theoretical groundwork for improving the learning capabilities of robots by combining various modes of learning subject to robot dynamics and stability constraints. The problem of active learning through experimental design, where anticipated sensor data is optimized, motivates the use of methods from ergodicity and ergodic exploration that enable robots to sample and sense from multiple information sources while simultaneously ensuring that the robot does not ignore unexplored parts of an environment. I illustrate the use of ergodicity as a promising approach for learning models in complex and spatially sparse environments using only rudimentary contact sensing. These results are extended to more general active learning in dynamic state-spaces where robot safety and the quality of informative measurements are balanced using hybrid control theoretic analysis and known stabilizing controllers. Last, I argue that we should not only care about active learning, but also how we model and represent the dynamics of robotic systems. The class of infinite linear embeddings is presented as a candidate model that simplifies and improves the control and active learning capabilities of robotic systems. Through simulated and experimental application, I illustrate the potential of the presented approaches for pushing the boundaries of robotic systems towards being more capable, self-sufficient, and curious systems that intentionally seek out the unknown and complex nature of interacting in our world.<br></div><div><br></div><div><b>Bio:</b> Ian Abraham is a Postdoctoral scholar at the Robotics Institute at Carnegie Mellon University. He received the B.S. degree in Mechanical and Aerospace Engineering from Rutgers University and the M.S. and Ph.D degree in Mechanical Engineering from Northwestern University at the Center for Robotics and Biosystems. His Ph.D. work focuses on developing formal methods for robot sensing and runtime active learning. During his Ph.D. he interned at the NVIDIA Seattle Robotics Lab where he worked on robust model-based control for large parameter uncertainty. He also participated in the DARPA OFFSET FX-3 Urban Swarm Challenge and is the recipient of the 2019 King-Sun Fu IEEE Transactions on Robotics Best Paper award.</div><div><br></div><div><b>Host:</b> <a href="mailto:mwalter@ttic.edu" target="_blank">Matthew Walter</a></div><div><br></div><div><br></div></div><div><div dir="ltr"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><font face="arial, helvetica, sans-serif">Mary C. Marre</font><div><font face="arial, helvetica, sans-serif">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">6045 S. Kenwood Avenue</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Room 517</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL 60637</font></i></div><div><i><font face="arial, helvetica, sans-serif">p:(773) 834-1757</font></i></div><div><i><font face="arial, helvetica, sans-serif">f: (773) 357-6970</font></i></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>
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