Robots should safely and correctly operate alongside uncontrollable agents such as humans. In domains involving uncontrollable agents, such as the scenario shown in Fig. 1, robots must react to changes online to ensure safety and accomplish desired tasks. Thus, rather than pre-programming finite instructions or pre-computing a single, linear plan, robots need a policy that determines the correc...

Working memory, the short-term maintenance and manipulation of information, relies strongly on neural activity in the frontal cortex. Understanding the functional role of this activity is a prerequisite for the understanding of cognitive control mechanisms. Functional imaging studies in human participants have attempted to reveal neural correlates of the subdivision of visual working memory int...

OBJECTIVE Patients with schizophrenia exhibit impairments in working memory that often appear in attenuated form in persons at high risk for the illness. The authors hypothesized that deviations in task-related brain activation and deactivation would occur in persons with an at-risk mental state performing a working memory task that entailed the maintenance and manipulation of letters. METHOD...

We propose to integrate tactile and visual sensing to predict task-compatible grasp regions for manipulation. We address the problem of fine-part assembly, by leveraging vision to observe scene-level information, then touch to perceive fine local details necessary for task completion. We directly target the end goal of task success, by predicting grasp regions that are simultaneously geometrica...

Introduction In order to design robots suited to engage in cooperative manipulation tasks with humans, we study human-human teams as they work together to move a heavy object across a room. We are interested in several questions. First, do two person, gross motion tasks follow the same sinusoidal pattern, one person fine motion tasks do? Does performance improve when audio or visual communicati...

We present an active learning approach that enables a mobile manipulator to autonomously learn task-relevant features. For a given behavior, our system trains a Support Vector Machine (SVM) that predicts the 3D locations at which the behavior will succeed. This decision is made based on visual features that surround each 3D location. After a quick initialization by the user, the robot efficient...

Although most part of the literature on manipulation systems deals with systems with as many degrees of freedom as the dimension of their task space, or even with more (redundant manipulators), kinematically defective manipulation systems are often encountered in robotics, in particular when dealing with simple industry– oriented grippers, or when the whole surface of the manipulator limbs is e...

This paper presents a scheme by which a manipulator can use dynamic tactile sensing to detect when it is about to lose hold of a grasped object and take preventive measures before gross sliding occurs. By detecting localized slips on the gripping surface which precede gross slip, the controller can modify the grasp force to prevent the object from slipping. Also, by monitoring normal and tangen...

Recent work suggests that human subjects may learn mappings between object motion and exerted torque during manipulation of freely pivoting or unstable objects. In the present work, we studied an object manipulation task involving no arm movement to determine how subjects internally represent the force-motion relationship of an object during a skilled manipulation task. Human subjects learned t...

|We present an interactive manipulation path planner under development for providing high-level task-based control for humanoid robots. Using a graphical simulation environment, the software is designed to facilitate the automation of object grasping and manipulation tasks. A randomized path planner is used to directly search the free con guration space of the robot for a collision-free manipul...