Training a machine learning algorithm on a class-imbalanced dataset can be a difficult task,
a process that could prove even more challenging under conditions of high dimensionality …

Grasping and assembly are essential tasks in high-precision robotic manipulation for
industrial manufacturing as well as for home service applications. Many efforts have been …

This paper proposes an end-to-end learning from demonstration framework for teaching
force-based manipulation tasks to robots. The strengths of this work are manyfold. First, we …

Training a machine learning algorithm from a class-imbalanced dataset is an inherently
challenging task. The task becomes more challenging when compounded by high …

Improving robot systems via newly-developed sensing devices, control algorithms, or state
estimators in order to obtain safe and efficient human-robot interaction as well as tactile …

Force feedback is necessary for accurate force control in robotic manipulators, and thus far,
wrist force/torque (F/T) sensors have been used. But an important problem arises when only …

In this paper, experimental implementation and comparative accuracy evaluation of five
methods for estimation of human-robot interaction torques are presented. These methods …

The estimation of the ten inertial parameters of rigid loads, which are attached to
manipulators, may benefit several robotics applications, eg: force control, object recognition …

Constant force control and smooth trajectory planning are regarded as key strategies to
improve the surface quality of blades in robotic abrasive belt grinding. However, some …

For tasks in robotic assembly, a basic requirement is the capability of the robotic system to
detect contacts with the environment. While this information can readily be obtained from …