text: We present and evaluate an approach for human-in-the-loop specification of shape reconstruction with annotations for basic robot-object interactions. Our method is based on the idea of model annotation: the addition of simple cues to an underlying object model to specify shape and delineate a simple task. The goal is to explore reducing the complexity of CAD-like interfaces so that novice users can quickly recover an object's shape and describe a manipulation task that is then carried out by a robot. The object modeling and interaction annotation capabilities are tested with a user study and compared against results obtained using existing approaches. The approach has been analyzed using a variety of shape comparison, grasping, and manipulation metrics, and tested with the PR2 robot platform, where it was shown to be successful.
  @cite_129: ''Shared Grasping'' describes a new approach to shared autonomy for grasping and manipulation tasks to be used in a telepresence system. It is realized with two assistance functionalities, which simplify the grasping, and a user interface, which merges haptic feedback and visual assistance. User studies confirm a reduction in operator workload and an increase in task performance while maintaining a high immersion of the operator into the remote environment when using the assistance functions.
  @cite_16: In human-robot comanipulation, virtual guides are an important tool used to assist the human worker by reducing physical effort and cognitive overload during tasks accomplishment. However, virtual guide's construction often requires expert knowledge and modeling of the task which restricts the usefulness of virtual guides to scenarios with unchanging constraints. To overcome these challenges and enhance the flexibility of virtual guide's programming, we present a novel approach that allows the worker to create virtual guides by demonstration through an iterative method based on kinesthetic teaching and Akima splines. Thanks to this approach, the worker is able to locally modify the guides while being assisted by them, increasing the intuitiveness and naturalness of the process. Finally, we evaluate our approach in a simulated sanding task with a collaborative robot.
  @cite_113: 
summary: One popular tool for motion planning is Moveit! @cite_113 . This tool can be used within the larger Robot Operating System (ROS) to perform automatic motion planning with collision avoidance. This may also be used in conjunction with a manipulation interface that humans can use to indicate motions. In the work by , @cite_16 , this interface was used to analyze manipulation strategies for indicating grasps and grasp approach methodologies. They compared continuous teleoperation against three other strategies with varying degrees of autonomy. They showed than a combination of manual annotation and automatic processing resulted in the greatest success rate. This is supported by the work done by Hertkorn @cite_129 , where the importance of shared workload is thoroughly analyzed in the context of grasping and manipulation.