18 citations · 32 across the 11 of their papers we have counts for
13 papers
A Model-Agnostic Approach for Semantically Driven Disambiguation in Human-Robot Interaction
Fethiye Irmak Dogan, Maithili Patel, Weiyu Liu +2
Ambiguities are inevitable in human-robot interaction, especially when a robot follows user instructions in a large, shared space. For example, if a user asks the robot to find an…
GraspGPT: Leveraging Semantic Knowledge from a Large Language Model for Task-Oriented Grasping
Chao Tang, Dehao Huang, Wenqi Ge +2
Task-oriented grasping (TOG) refers to the problem of predicting grasps on an object that enable subsequent manipulation tasks. To model the complex relationships between objects,…
Latent Space Planning for Multi-Object Manipulation with Environment-Aware Relational Classifiers
Yixuan Huang, Nichols Crawford Taylor, Adam Conkey +2
Objects rarely sit in isolation in everyday human environments. If we want robots to operate and perform tasks in our human environments, they must understand how the objects they…
Task-Oriented Grasp Prediction with Visual-Language Inputs
Chao Tang, Dehao Huang, Lingxiao Meng +2
To perform household tasks, assistive robots receive commands in the form of user language instructions for tool manipulation. The initial stage involves selecting the intended too…
StructDiffusion: Language-Guided Creation of Physically-Valid Structures using Unseen Objects
Weiyu Liu, Yilun Du, Tucker Hermans +2
Robots operating in human environments must be able to rearrange objects into semantically-meaningful configurations, even if these objects are previously unseen. In this work, we…
StructFormer: Learning Spatial Structure for Language-Guided Semantic Rearrangement of Novel Objects
Weiyu Liu, Chris Paxton, Tucker Hermans +1
Geometric organization of objects into semantically meaningful arrangements pervades the built world. As such, assistive robots operating in warehouses, offices, and homes would gr…
Towards Robust One-shot Task Execution using Knowledge Graph Embeddings
Angel Daruna, Lakshmi Nair, Weiyu Liu +1
Requiring multiple demonstrations of a task plan presents a burden to end-users of robots. However, robustly executing tasks plans from a single end-user demonstration is an ongoin…
Same Object, Different Grasps: Data and Semantic Knowledge for Task-Oriented Grasping
Adithyavairavan Murali, Weiyu Liu, Kenneth Marino +2
Despite the enormous progress and generalization in robotic grasping in recent years, existing methods have yet to scale and generalize task-oriented grasping to the same extent. T…
Taking Recoveries to Task: Recovery-Driven Development for Recipe-based Robot Tasks
Siddhartha Banerjee, Angel Daruna, David Kent +9
Robot task execution when situated in real-world environments is fragile. As such, robot architectures must rely on robust error recovery, adding non-trivial complexity to highly-c…
CAGE: Context-Aware Grasping Engine
Weiyu Liu, Angel Daruna, Sonia Chernova
Semantic grasping is the problem of selecting stable grasps that are functionally suitable for specific object manipulation tasks. In order for robots to effectively perform object…
Leveraging Semantics for Incremental Learning in Multi-Relational Embeddings
Angel Daruna, Weiyu Liu, Zsolt Kira +1
Service robots benefit from encoding information in semantically meaningful ways to enable more robust task execution. Prior work has shown multi-relational embeddings can encode s…
Path Ranking with Attention to Type Hierarchies
Weiyu Liu, Angel Daruna, Zsolt Kira +1
The objective of the knowledge base completion problem is to infer missing information from existing facts in a knowledge base. Prior work has demonstrated the effectiveness of pat…
RoboCSE: Robot Common Sense Embedding
Angel Daruna, Weiyu Liu, Zsolt Kira +1
Autonomous service robots require computational frameworks that allow them to generalize knowledge to new situations in a manner that models uncertainty while scaling to real-world…