Alap Kshirsagar — accepted AI-conference papers

2024

MoVEInt: Mixture of Variational Experts for Learning Human-Robot Interactions From Demonstrations

Vignesh Prasad, Alap Kshirsagar, Dorothea Koert, Ruth Stock-Homburg, Jan Peters, Georgia Chalvatzaki

RA-L 2024

Shared dynamics models are important for capturing the complexity and variability inherent in Human-Robot Interaction (HRI). Therefore, learning such shared dynamics models can enhance coordination and adaptability to enable successful reactive interactions with a human partner. In this work, we pro

Cited by 11 Source ↗code ↗Scholar ↗

2024

What Matters for Active Texture Recognition With Vision-Based Tactile Sensors

Alina Böhm, Tim Schneider, Boris Belousov, Alap Kshirsagar, Lisa Lin, Katja Doerschner +3

ICRA 2024poster

This paper explores active sensing strategies that employ vision-based tactile sensors for robotic perception and classification of fabric textures. We formalize the active sampling problem in the context of tactile fabric recognition and provide an implementation of information-theoretic exploratio…

Cited by 7 Source ↗Scholar ↗

2021

Evaluating Guided Policy Search for Human-Robot Handovers

Alap Kshirsagar, Guy Hoffman, Armin Biess

RA-L 2021

We evaluate the potential of Guided Policy Search (GPS), a model-based reinforcement learning (RL) method, to train a robot controller for human-robot object handovers. Handovers are a key competency for collaborative robots and GPS could be a promising approach for this task, as it is data efficien

Cited by 15 Source ↗Scholar ↗

2020

Robot Gaze Behaviors in Human-to-Robot Handovers

Alap Kshirsagar, Melanie Lim, Shemar Christian, Guy Hoffman

RA-L 2020

We present the results of two studies investigating gaze behaviors of a robot receiving an object from a human. Robot gaze is an important nonverbal behavior during human-robot handovers, yet prior work has only studied robots as givers. From a frame-by-frame video analysis of human-human handovers,

Cited by 27 Source ↗Scholar ↗

2019

Specifying and Synthesizing Human-Robot Handovers

Alap Kshirsagar, Hadas Kress-Gazit, Guy Hoffman

IROS 2019poster

We present a controller for human-robot handovers that is automatically synthesized from high-level specifications in Signal Temporal Logic (STL). In contrast to existing controllers, this approach can provide formal guarantees on the timing of each of the handover phases. Using synthesis also allow…

Cited by 42 Source ↗Scholar ↗