세미나 Towards Long-Horizon Robot Decision Making (성윤창 박사 / Postdoctoral fell…
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작성자 최고관리자 작성일 24-08-09 14:53본문
날짜 : 2024년 8월 22일 (목) 11:00~12:00
장소 : 공학원 452B
Abstract: Solving long-horizon tasks involving the manipulation of multiple objects, such as cleaning a dirty room and preparing a meal, has long been a grand challenge in robotics. These tasks present significant challenges in selecting high-level actions, like picking up a cup, and effectively planning how to achieve these actions while satisfying physical and geometric constraints. Existing algorithms are prohibitively expensive to scale beyond the smallest problems, and these planning costs remain a significant bottleneck in advancing the capabilities of robots.
In this talk, I will discuss task and motion planning (TAMP), a general planning framework that exhibits a bilevel structure: high-level task reasoning (i.e., determining which actions to take) and low-level motion reasoning (i.e., determining how to execute these actions) mutually provide complementary guidance. I will introduce the fundamental challenges preventing the deployment of existing TAMP approaches to long-horizon problems in practice. To address these challenges, I will present research contributions to enhance efficiency, such as designing a new data structure and leveraging machine learning techniques. I will then discuss two important extensions to the TAMP framework: deadline-aware TAMP and multi-robot TAMP. I will conclude the talk by proposing future research directions that can move toward the real-world deployment of robots in challenging unstructured environments.
Bio: Yoonchang Sung is a postdoctoral fellow at UT Austin, working with Peter Stone, and was previously a postdoctoral associate at MIT CSAIL, working with Leslie Kaelbling and Tomás Lozano-Pérez. He completed his Ph.D. at Virginia Tech, advised by Pratap Tokekar. His research interests include robot planning and learning, task and motion planning, and multi-robot systems. He was selected as one of the RSS Pioneers in 2019. His work was nominated for the Best Cognitive Robotics Paper Award and received the Best Robocup Paper Award, both at IROS 2021.
장소 : 공학원 452B
Title: Towards Long-Horizon Robot Decision Making
Abstract: Solving long-horizon tasks involving the manipulation of multiple objects, such as cleaning a dirty room and preparing a meal, has long been a grand challenge in robotics. These tasks present significant challenges in selecting high-level actions, like picking up a cup, and effectively planning how to achieve these actions while satisfying physical and geometric constraints. Existing algorithms are prohibitively expensive to scale beyond the smallest problems, and these planning costs remain a significant bottleneck in advancing the capabilities of robots.
In this talk, I will discuss task and motion planning (TAMP), a general planning framework that exhibits a bilevel structure: high-level task reasoning (i.e., determining which actions to take) and low-level motion reasoning (i.e., determining how to execute these actions) mutually provide complementary guidance. I will introduce the fundamental challenges preventing the deployment of existing TAMP approaches to long-horizon problems in practice. To address these challenges, I will present research contributions to enhance efficiency, such as designing a new data structure and leveraging machine learning techniques. I will then discuss two important extensions to the TAMP framework: deadline-aware TAMP and multi-robot TAMP. I will conclude the talk by proposing future research directions that can move toward the real-world deployment of robots in challenging unstructured environments.
Bio: Yoonchang Sung is a postdoctoral fellow at UT Austin, working with Peter Stone, and was previously a postdoctoral associate at MIT CSAIL, working with Leslie Kaelbling and Tomás Lozano-Pérez. He completed his Ph.D. at Virginia Tech, advised by Pratap Tokekar. His research interests include robot planning and learning, task and motion planning, and multi-robot systems. He was selected as one of the RSS Pioneers in 2019. His work was nominated for the Best Cognitive Robotics Paper Award and received the Best Robocup Paper Award, both at IROS 2021.
Website: https://yoonchangsung.com/
관련링크
- https://yoonchangsung.com/ 261회 연결
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