Manipulation

[IROS22] Sequential Manipulation Planning on Scene Graph

We devise a 3D scene graph representation, contact graph+ (cg+), for efficient sequential manipulation planning. Augmented with …

Ziyuan Jiao, Yida Niu, Zeyu Zhang, Song-Chun Zhu, Yixin Zhu, Hangxin Liu

[IROS22] Sequential Manipulation Planning on Scene Graph

[RA-L/IROS22] Understanding Physical Effects for Effective Tool-use

We present a robot learning and planning framework that produces an effective tool-use strategy with the least joint efforts, capable …

Zeyu Zhang, Ziyuan Jiao, Weiqi Wang, Yixin Zhu, Song-Chun Zhu, Hangxin Liu

[RA-L/IROS22] Understanding Physical Effects for Effective Tool-use

[RA-L21] Synthesizing Diverse and Physically Stable Grasps with Arbitrary Hand Structures using Differentiable Force Closure Estimator

Existing grasp synthesis methods are either analytical or data-driven. The former one is oftentimes limited to specific application …

Tengyu Liu, Zeyu Liu, Ziyuan Jiao, Yixin Zhu, Song-Chun Zhu

[RA-L21] Synthesizing Diverse and Physically Stable Grasps with Arbitrary Hand Structures using Differentiable Force Closure Estimator

[IROS21] Consolidating Kinematic Models to Promote Coordinated Mobile Manipulations

We construct a Virtual Kinematic Chain (VKC) that readily consolidates the kinematics of the mobile base, the arm, and the object to be …

Ziyuan Jiao, Zeyu Zhang, Xin Jiang, David Han, Song-Chun Zhu, Yixin Zhu, Hangxin Liu

[IROS21] Consolidating Kinematic Models to Promote Coordinated Mobile Manipulations

[IROS21] Efficient Task Planning for Mobile Manipulation: a Virtual Kinematic Chain Perspective

We present a Virtual Kinematic Chain (VKC) perspective, a simple yet effective method, to improve task planning efficacy for mobile …

Ziyuan Jiao, Zeyu Zhang, Weiqi Wang, David Han, Song-Chun Zhu, Yixin Zhu, Hangxin Liu

[IROS21] Efficient Task Planning for Mobile Manipulation: a Virtual Kinematic Chain Perspective

[IROS19] Learning Virtual Grasp with Failed Demonstrations via Bayesian Inverse Reinforcement Learning

We propose Bayesian Inverse Reinforcement Learning with Failure (BIRLF), which makes use of failed demonstrations that were often …

Xu Xie, Changyang Li, Chi Zhang, Yixin Zhu, Song-Chun Zhu

[IROS19] Learning Virtual Grasp with Failed Demonstrations via Bayesian Inverse Reinforcement Learning

[ICRA19] High-Fidelity Grasping in Virtual Reality using a Glove-based System

This paper presents a design that jointly provides hand pose sensing, hand localization, and haptic feedback to facilitate real-time …

Hangxin Liu, Zhenliang Zhang, Xu Xie, Yixin Zhu, Yue Liu, Yongtian Wang, Song-Chun Zhu

[ICRA19] High-Fidelity Grasping in Virtual Reality using a Glove-based System

[AAAI19] Mirroring without Overimitation: Learning Functionally Equivalent Manipulation Actions

This paper presents a mirroring approach, inspired by the neuroscience discovery of the mirror neurons, to transfer demonstrated …

Hangxin Liu, Chi Zhang, Yixin Zhu, Chenfanfu Jiang, Song-Chun Zhu

[AAAI19] Mirroring without Overimitation: Learning Functionally Equivalent Manipulation Actions

[ICRA18] Unsupervised Learning using Hierarchical Models for Hand-Object Interactions

Contact forces of the hand are visually unobservable, but play a crucial role in understanding hand-object interactions. In this paper, …

Xu Xie, Hangxin Liu, Mark Edmonds, Feng Gao, Siyuan Qi, Yixin Zhu, Brandon Rothrock, Song-Chun Zhu

[ICRA18] Unsupervised Learning using Hierarchical Models for Hand-Object Interactions