Student Talks
Carnegie Mellon University
Liquid Metal Actuators
Abstract: This thesis contributes to the field of soft actuators by introducing a generalized framework of actuators from liquid metals. The evolution of robotic actuators has enabled robots to achieve a diversity of motions. Like natural muscles, which converts chemical energy into mechanical work in response to electrical stimuli from the nervous system, actuators are [...]
Continual Robot Learning: Benchmarks and Modular Methods
Zoom Meeting Passcode: 841755 Abstract: The earliest reinforcement learning models were designed to learn one task, specified up-front. However, an agent operating freely in the real world will not in general be granted this luxury, as the demands placed on the agent may change as environments or goals change. We refer to this ever-shifting scenario [...]
Carnegie Mellon University
MSR Thesis Talk: Yash Oza
Title: Preprocessing-based Methods for Robotic Manipulation Abstract: Robotic manipulation is a key problem for several applications such as welding, pick-and-place, and automated assembly. However, motion planning for manipulation can be computationally expensive as it requires planning in the high-dimensional configuration space of the manipulator. Additionally, task-specific constraints such as strict time limits or constraints on end-effector [...]
MSR Thesis Talk: Ingrid Navarro Anaya
Title: Socially-Aware Trajectory Prediction Guided by Motion Patterns Abstract: As intelligent robots across domains start collaborating with humans in shared environments, e.g., urban settings and terminal airspace, algorithms that enable them to reason over human motion and intent are important to enable seamless and safe interplay. In our work, we study human intent by focusing on the [...]
Carnegie Mellon University
MSR Thesis Talk: Qichen Fu
Date: Tuesday, July 19, 2022 Time: 9:00 AM - 10:00 AM ET Location: Newell-Simon Hall (NSH) 3305 Title: Detect Active Object in a Sequential Voting Process Abstract: A key component of understanding hand-object interactions is the ability to identify the active object -- the object that is being manipulated by the human hand. In order to accurately localize the [...]
Carnegie Mellon University
MSR Thesis Talk: Ruohai Ge
Title: Real-Time Visual Localization System in Changing and Challenging Environments via Visual Place Recognition Abstract: Localization is one of the fundamental capabilities to guarantee reliable robot autonomy. Many excellent Visual-Inertial and LiDAR-based algorithms have been developed to solve the localization problem. However, deploying these methods on a real-time portable device is challenging due to high [...]
Carnegie Mellon University
MSR Thesis Talk – Zixuan Huang
Title: Seeing the Unseen: Closed-loop Occlusion Reasoning for Cloth Manipulation Robotic manipulation of cloth remains challenging due to the complex dynamics of cloth, lack of a low-dimensional state representation, and self-occlusions. Particularly, self-occlusion makes it difficult to estimate the full state of the cloth, which poses significant challenges to policy learning and dynamics modeling. Ideally, [...]
Carnegie Mellon University
MSR Thesis Talk – Zhaoyuan Fang
Title: Features in Extra Dimensions: Spatial and Temporal Scene Representations Abstract: Computer vision models have made great progress in featurizing pixels of images. However, an image is only a projection of the actual 3D scene: occlusions and perspective distortions exist. To arrive at a better representation of the scene itself, extra dimensions are needed to [...]
Carnegie Mellon University
MSR Thesis Talk – Yunchu Zhang
Title: Library of behaviors and tools for robot manipulation Abstract: Learned policies often fail to generalize across environment variations, such as, different objects, object arrangements, or camera viewpoints. Moreover, most policies are trained and tested in simulation environments, and the sim2real gap remains large under weak visual representations that do not disentangle the scene from [...]
Carnegie Mellon University
Learning Structured World Model for Deformable Object Manipulation
Abstract: Manipulation of deformable objects challenges common assumptions in robotic manipulation, such as low-dimension state representation, known dynamics, and minimal occlusion. Deformable objects have high intrinsic state representation, complex dynamics with high degrees of freedom, and severe self-occlusion. These properties make them difficult for state estimation and planning. In this thesis, we introduce benchmarks and [...]