  Designing robotic assistance devices for manipulation tasks is challenging.
This work is concerned with improving accuracy and usability of semi-autonomous
robots, such as human operated manipulators or exoskeletons. The key insight is
to develop a system that takes into account context- and user-awareness to take
better decisions in how to assist the user. The context-awareness is
implemented by enabling the system to automatically generate a set of candidate
grasps and reach-to-grasp trajectories in novel, cluttered scenes. The
user-awareness is implemented as a linear time-variant feedback controller to
facilitate the motion towards the most promising grasp. Our approach is
demonstrated in a simple 2D example in which participants are asked to grasp a
specific object in a clutter scene. Our approach also reduce the number of
controllable dimensions for the user by providing only control on x- and
y-axis, while orientation of the end-effector and the pose of its fingers are
inferred by the system. The experimental results show the benefits of our
approach in terms of accuracy and execution time with respect to a pure manual
control.
