21 citations · 32 across the 8 of their papers we have counts for
6 papers · 1 filter
Stimulate the Potential of Robots via Competition
Kangyao Huang, Di Guo, Xinyu Zhang +2
It is common for us to feel pressure in a competition environment, which arises from the desire to obtain success comparing with other individuals or opponents. Although we might g…
Audio-Visual Grounding Referring Expression for Robotic Manipulation
Yefei Wang, Kaili Wang, Yi Wang +3
Referring expressions are commonly used when referring to a specific target in people's daily dialogue. In this paper, we develop a novel task of audio-visual grounding referring e…
Knowledge-based Embodied Question Answering
Sinan Tan, Mengmeng Ge, Di Guo +2
In this paper, we propose a novel Knowledge-based Embodied Question Answering (K-EQA) task, in which the agent intelligently explores the environment to answer various questions wi…
Fault-Aware Robust Control via Adversarial Reinforcement Learning
Fan Yang, Chao Yang, Di Guo +2
Robots have limited adaptation ability compared to humans and animals in the case of damage. However, robot damages are prevalent in real-world applications, especially for robots…
Adversarial Skill Learning for Robust Manipulation
Pingcheng Jian, Chao Yang, Di Guo +2
Deep reinforcement learning has made significant progress in robotic manipulation tasks and it works well in the ideal disturbance-free environment. However, in a real-world enviro…
Towards Embodied Scene Description
Sinan Tan, Huaping Liu, Di Guo +2
Embodiment is an important characteristic for all intelligent agents (creatures and robots), while existing scene description tasks mainly focus on analyzing images passively and t…