28 citations · 92 across the 41 of their papers we have counts for
8 papers · 1 filter
Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection
Xinghao Zhu, Devesh K. Jha, Diego Romeres +3
Automating the assembly of objects from their parts is a complex problem with innumerable applications in manufacturing, maintenance, and recycling. Unlike existing research, which…
Interactive Planning Using Large Language Models for Partially Observable Robotics Tasks
Lingfeng Sun, Devesh K. Jha, Chiori Hori +5
Designing robotic agents to perform open vocabulary tasks has been the long-standing goal in robotics and AI. Recently, Large Language Models (LLMs) have achieved impressive result…
A Black-Box Physics-Informed Estimator based on Gaussian Process Regression for Robot Inverse Dynamics Identification
Giulio Giacomuzzos, Ruggero Carli, Diego Romeres +1
Learning the inverse dynamics of robots directly from data, adopting a black-box approach, is interesting for several real-world scenarios where limited knowledge about the system…
Forward Dynamics Estimation from Data-Driven Inverse Dynamics Learning
Alberto Dalla Libera, Giulio Giacomuzzo, Ruggero Carli +2
In this paper, we propose to estimate the forward dynamics equations of mechanical systems by learning a model of the inverse dynamics and estimating individual dynamics components…
Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos
Chiori Hori, Puyuan Peng, David Harwath +7
To realize human-robot collaboration, robots need to execute actions for new tasks according to human instructions given finite prior knowledge. Human experts can share their knowl…
Learning Generalizable Pivoting Skills
Xiang Zhang, Siddarth Jain, Baichuan Huang +2
The skill of pivoting an object with a robotic system is challenging for the external forces that act on the system, mainly given by contact interaction. The complexity increases w…
Simultaneous Tactile Estimation and Control of Extrinsic Contact
Sangwoon Kim, Devesh K. Jha, Diego Romeres +2
We propose a method that simultaneously estimates and controls extrinsic contact with tactile feedback. The method enables challenging manipulation tasks that require controlling l…
Learning Control from Raw Position Measurements
Fabio Amadio, Alberto Dalla Libera, Daniel Nikovski +2
We propose a Model-Based Reinforcement Learning (MBRL) algorithm named VF-MC-PILCO, specifically designed for application to mechanical systems where velocities cannot be directly…