6 citations · 19 across the 11 of their papers we have counts for
11 papers
OVAL-Grasp: Open-Vocabulary Affordance Localization for Task Oriented Grasping
Edmond Tong, Advaith Balaji, Anthony Opipari +3
To manipulate objects in novel, unstructured environments, robots need task-oriented grasps that target object parts based on the given task. Geometry-based methods often struggle…
OVAL-Prompt: Open-Vocabulary Affordance Localization for Robot Manipulation through LLM Affordance-Grounding
Edmond Tong, Anthony Opipari, Stanley Lewis +2
In order for robots to interact with objects effectively, they must understand the form and function of each object they encounter. Essentially, robots need to understand which act…
Probabilistic Inference in Planning for Partially Observable Long Horizon Problems
Alphonsus Adu-Bredu, Nikhil Devraj, Pin-Han Lin +2
For autonomous service robots to successfully perform long horizon tasks in the real world, they must act intelligently in partially observable environments. Most Task and Motion P…
SeanNet: Semantic Understanding Network for Localization Under Object Dynamics
Xiao Li, Yidong Du, Zhen Zeng +1
We aim for domestic robots to perform long-term indoor service. Under the object-level scene dynamics induced by daily human activities, a robot needs to robustly localize itself i…
Elephants Don't Pack Groceries: Robot Task Planning for Low Entropy Belief States
Alphonsus Adu-Bredu, Zhen Zeng, Neha Pusalkar +1
Recent advances in computational perception have significantly improved the ability of autonomous robots to perform state estimation with low entropy. Such advances motivate a reco…
Manipulation-Oriented Object Perception in Clutter through Affordance Coordinate Frames
Xiaotong Chen, Kaizhi Zheng, Zhen Zeng +5
In order to enable robust operation in unstructured environments, robots should be able to generalize manipulation actions to novel object instances. For example, to pour and serve…
Semantic Linking Maps for Active Visual Object Search
Zhen Zeng, Adrian Röfer, Odest Chadwicke Jenkins
We aim for mobile robots to function in a variety of common human environments. Such robots need to be able to reason about the locations of previously unseen target objects. Landm…
Semantic Mapping with Simultaneous Object Detection and Localization
Zhen Zeng, Yunwen Zhou, Odest Chadwicke Jenkins +1
We present a filtering-based method for semantic mapping to simultaneously detect objects and localize their 6 degree-of-freedom pose. For our method, called Contextual Temporal Ma…
Semantic Robot Programming for Goal-Directed Manipulation in Cluttered Scenes
Zhen Zeng, Zheming Zhou, Zhiqiang Sui +1
We present the Semantic Robot Programming (SRP) paradigm as a convergence of robot programming by demonstration and semantic mapping. In SRP, a user can directly program a robot ma…
SUM: Sequential Scene Understanding and Manipulation
Zhiqiang Sui, Zheming Zhou, Zhen Zeng +1
In order to perform autonomous sequential manipulation tasks, perception in cluttered scenes remains a critical challenge for robots. In this paper, we propose a probabilistic appr…
Object Manipulation Learning by Imitation
Zhen Zeng, Benjamin Kuipers
We aim to enable robot to learn object manipulation by imitation. Given external observations of demonstrations on object manipulations, we believe that two underlying problems to…