Productive human-robot partnerships are vital to successful integration of assistive robots into everyday life. While prior research has explored techniques facilitate collaboration during interaction, the work described here aims forge productive drawing upon team building activities’ aid in establishing effective human teams. Through a 2 (group membership: ingroup and outgroup) × 3 (robot err...

Humans are capable of accomplishing a variety of complex tasks in environments which have continu ously changing characteristics Robots however gen erally require highly structured environments which al low the programmer to make a large number of as sumptions making the robot s task easier to encode We propose a framework for programming robotic tasks using human to robot skill transfer We ass...

This letter presents a resilient mechanism to allocate heterogeneous robots tasks under difficult environmental conditions such as weather events or adversarial attacks. Our primary objective is ensure that each task assigned the requisite level of resources, measured aggregated capabilities allocated task. By keeping track performance deviations external perturbations, our framework quantifies...

Endowing robots with the human ability to learn a growing set of skills over course lifetime as opposed mastering single tasks is an open problem in robot learning. While multi-task learning approaches have been proposed address this problem, they pay little attention task inference. In order continually new tasks, first needs infer at hand without requiring predefined representations. paper, w...

Several research efforts have addressed the challenge of having non-technical users teach or demonstrate a task to a robot, focusing on the teaching method and the task acquisition. In this paper, we consider an autonomous robot that persists over time interacting with users and the problem of teaching an additional task to the robot. We believe that the assumption that a user would know all th...

The goal of robot learning from demonstration is to have a robot learn from watching a demonstration of the task to be performed. In our approach to learning from demonstration the robot learns a reward function from the demonstration and a task model from repeated attempts to perform the task. A policy is computed based on the learned reward function and task model. Lessons learned from an imp...

Several research efforts address the challenge of having users incrementally teach or demonstrate a task to a robot. We are interested in an autonomous robot that persists over time and the problem of teaching it an additional task. We believe that the assumption that a user would know all the tasks previously taught to the robot does not hold. We hence investigate the problem of recognizing wh...