Abstract Models are among the most essential tools in robotics, such as kinematics and
dynamics models of the robot's own body and controllable external objects. It is widely …

The rise of deep learning has caused a paradigm shift in robotics research, favoring
methods that require large amounts of data. Unfortunately, it is prohibitively expensive to …

A new adaptive robot control algorithm is derived, which consists of a PD feedback part and
a full dynamics feedfor ward compensation part, with the unknown manipulator and payload …

The singularity problem is an inherent problem in controlling robot manipulators with
articulated configuration. In this paper, we propose to determine the joint motion for the …

For parameter identifications of robot systems, most existing works have focused on the
estimation veracity, but few works of literature are concerned with the convergence speed. In …

The author's previous work (1986, 1987) utilized the particular structure of manipulator
dynamics to develop a simple, globally convergent adaptive controller for manipulator …

This paper discusses experimental robot identification based on a statistical framework. It
presents a new approach toward the design of optimal robot excitation trajectories, and …

One of the fundamental requirements for the success of a robot task is the capability to
handle interaction between manipulator and environment. The quantity that describes the …

Designing controllers for tasks with complex nonlinear dynamics is extremely challenging,
time-consuming, and in many cases, infeasible. This difficulty is exacerbated in tasks such …

Recent approaches in robot perception follow the insight that perception is facilitated by
interaction with the environment. These approaches are subsumed under the term …