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 …

Common methods for learning robot dynamics assume motion is continuous, causing
unrealistic model predictions for systems undergoing discontinuous impact and stiction …

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 shared grasp is a grasp formed by contacts between the manipulated object and both the
robot hand and the environment. By trading off hand contacts for environmental contacts, a …

The central theme in robotic manipulation is that of the robot interacting with the world
through physical contact. We tend to describe that physical contact using specific words that …

Despite decades of research robotic manipulation systems outside of highly structured
industrial applications are still far from ubiquitous. Perhaps particularly curious is the fact that …

Complex dexterous manipulations require switching between prehensile and non-
prehensile grasps, and sliding and pivoting the object against the environment. This paper …

Control techniques like MPC can realize contact-rich manipulation which exploits dynamic
information, maintaining friction limits and safety constraints. However, contact geometry and …

Within the field of robotic manipulation, a central goal is to replicate the human ability to
manipulate any object in any situation using a sequence of manipulation primitives such as …