most citedRecognizing Intent in Collaborative Manipulation

3 citations · 4 across the 5 of their papers we have counts for

collaborators

6 papers

cs.IT2024

Higher-order Interpretations of Deepcode, a Learned Feedback Code

Yingyao Zhou, Natasha Devroye, Gyorgy Turan +1

We present an interpretation of Deepcode, a learned feedback code that showcases higher-order error correction relative to an earlier interpretable model. By interpretation, we mea…

cs.RO20231 cited

Proactive Robot Control for Collaborative Manipulation Using Human Intent

Zhanibek Rysbek, Siyu Li, Afagh Mehri Shervedani +1

Collaborative manipulation task often requires negotiation using explicit or implicit communication. An important example is determining where to move when the goal destination is…

cs.RO20233 cited

Recognizing Intent in Collaborative Manipulation

Zhanibek Rysbek, Ki Hwan Oh, Milos Zefran

Collaborative manipulation is inherently multimodal, with haptic communication playing a central role. When performed by humans, it involves back-and-forth force exchanges between…

cs.IT2023

Interpreting Training Aspects of Deep-Learned Error-Correcting Codes

N. Devroye, A. Mulgund, R. Shekhar +3

As new deep-learned error-correcting codes continue to be introduced, it is important to develop tools to interpret the designed codes and understand the training process. Prior wo…

cs.RO2023

An End-to-End Human Simulator for Task-Oriented Multimodal Human-Robot Collaboration

Afagh Mehri Shervedani, Siyu Li, Natawut Monaikul +3

This paper proposes a neural network-based user simulator that can provide a multimodal interactive environment for training Reinforcement Learning (RL) agents in collaborative tas…

cs.RO2022

Group-based control of large-scale micro-robot swarms with on-board Physical Finite-State Machines

Siyu Li, Milos Zefran, Igor Paprotny

An important problem in microrobotics is how to control a large group of microrobots with a global control signal. This paper focuses on controlling a large-scale swarm of MicroStr…