Abstract Learning from Demonstration (LfD) is an efficient technique for robots to acquire
new skills through expert observation, significantly mitigating the need for laborious manual …

The empirical success of reinforcement learning (RL) in contact-rich manipulation leaves
much to be understood from a model-based perspective, where the key difficulties are often …

With the increasing demand for the dexterity of robotic operation, dexterous manipulation of
multi-fingered robotic hands with reinforcement learning is an interesting subject in the field …

In-hand object reorientation is necessary for performing many dexterous manipulation tasks,
such as tool use in less structured environments, which remain beyond the reach of current …

We present a novel method for global motion planning of robotic systems that interact with
the environment through contacts. Our method directly handles the hybrid nature of such …

This paper presents Contact Mode Guided Manipulation Planning (CMGMP) for 3D
quasistatic and quasi-dynamic rigid body motion planning in dexterous manipulation. The …

Planning robot dexterity is challenging due to the non-smoothness introduced by contacts,
intricate fine motions, and ever-changing scenarios. We present a hierarchical planning …

A primary challenge in robotic tool use is achieving precise manipulation with dexterous
robotic hands to mimic human actions. It requires understanding human tool use and …

Mixed‐integer model predictive control (MI‐MPC) can be a powerful tool for controlling
hybrid systems. In case of a linear‐quadratic objective in combination with linear or …

Robots often have to perform manipulation tasks in close proximity to people (Fig 1). As
such, it is desirable to use a robot arm that has limited joint torques so as to not injure the …