Organizational Unit:

Mobile Robot Laboratory

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https://hdl.handle.net/1853/70779

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Organizational Unit

College of Computing

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https://finding-aids.library.gatech.edu/agents/corporate_entities/1110

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Publication Search Results

Now showing 1 - 10 of 57

Temporal Heterogeneity and the Value of Slowness in Robotic Systems

(Georgia Institute of Technology, 2015-12) Arkin, Ronald C. ; Egerstedt, Magnus B.

Robot teaming is a well-studied area, but little research to date has been conducted on the fundamental benefits of heterogeneous teams and virtually none on temporal heterogeneity, where timescales of the various platforms are radically different. This paper explores this aspect of robot ecosystems consisting of fast and slow robots (SlowBots) working together, including the bio-inspiration for such systems.
Probabilistic Verification of Multi-robot Missions in Uncertain Environments

(Georgia Institute of Technology, 2015-11) Lyons, Damian M. ; Arkin, Ronald C. ; Jiang, Shu ; Harrington, Dagan ; Tang, Feng ; Tang, Peng

The effective use of autonomous robot teams in highly-critical missions depends on being able to establish performance guarantees. However, establishing a guarantee for the behavior of an autonomous robot operating in an uncertain environment with obstacles is a challenging problem. This paper addresses the challenges involved in building a software tool for verifying the behavior of a multi-robot waypoint mission that includes uncertain environment geometry as well as uncertainty in robot motion. One contribution of this paper is an approach to the problem of apriori specification of uncertain environments for robot program verification. A second contribution is a novel method to extend the Bayesian Network formulation to reason about random variables with different subpopulations, introduced to address the challenge of representing the effects of multiple sensory histories when verifying a robot mission. The third contribution is experimental validation results presented to show the effectiveness of this approach on a two-robot, bounding overwatch mission.
Mixed-Initiative Human-Robot Interaction: Definition, Taxonomy, and Survey

(Georgia Institute of Technology, 2015-10) Jiang, Shu ; Arkin, Ronald C.

The objectives of this article are: 1) to present a taxonomy for mixed-initiative human-robot interaction and 2) to survey its state of practice through the examination of past research along each taxonomical dimension. The paper starts with some definitions of mixed-initiative interaction (MII) from the perspective of human-computer interaction (HCI) to introduce the basic concepts of MII. We then synthesize these definitions to the robotic context for mixed-initiative human-robot teams. A taxonomy for mixed-initiative in human-robot interaction is then presented. The goal of the taxonomy is to inform the design of mixed-initiative human-robot systems by identifying key elements of these systems. The state of practice of mixed-initiative human-robot interaction is then surveyed and examined along each taxonomical dimension.
Towards a Robot Computational Model to Preserve Dignity in Stigmatizing Patient-Caregiver Relationships

(Georgia Institute of Technology, 2015-10) Pettinati, Michael J. ; Arkin, Ronald C.

Parkinson’s disease (PD) patients with an expressive mask are particularly vulnerable to stigmatization during interactions with their caregivers due to their inability to express affect through nonverbal channels. Our approach to uphold PD patient dignity is through the use of an ethical robot that mediates patient shame when it recognizes norm violations in the patient-caregiver interaction. This paper presents the basis for a computational model tasked with computing patient shame and the empathetic response of a caregiver during “empathetic opportunities” in their interaction. A PD patient is liable to suffer indignity when there is a substantial difference between his experienced shame and the empathy shown by the caregiver. When this difference falls outside of acceptable set bounds (norms), the robotic agent will act using subtle, nonverbal cues to guide the relationship back within these bounds, preserving patient dignity.
The Benefits of Robot Deception in Search and Rescue: Computational Approach for Deceptive Action Selection via Case-Based Reasoning

(Georgia Institute of Technology, 2015-10) Shim, Jaeeun ; Arkin, Ronald C.

By increasing the use of autonomous rescue robots in search and rescue (SAR), the chance of interaction between rescue robots and human victims also grows. More specifically, when autonomous rescue robots are considered in SAR, it is important for robots to handle sensitively human victims’ emotions. Deception can potentially be used effectively by robots to control human victims’ fear and shock as used by human rescuers. In this paper, we introduce robotic deception in SAR contexts and present a novel computational approach for an autonomous rescue robot’s deceptive action selection mechanism.
Primate-inspired Autonomous Navigation Using Mental Rotation and Advice-Giving

(Georgia Institute of Technology, 2015-09) Velayudhan, Lakshmi ; Arkin, Ronald C.

The cognitive process that enables many primate species to efficiently traverse their environment has been a subject of numerous studies. Mental rotation is hypothesized to be one such process. The evolutionary causes for dominance in primates of mental rotation over its counterpart, rotational invariance, is still not conclusively understood. Advice-giving offers a possible explanation for this dominance in more evolved primate species such as humans. This project aims at exploring the relationship between advice-giving and mental rotation by designing a system that combines the two processes in order to achieve successful navigation to a goal location. Two approaches to visual advice-giving were explored namely, segment based and object based advice-giving. The results obtained upon execution of the navigation algorithm on a Pioneer 2-DX robotic platform offers evidence regarding a linkage between advice-giving and mental rotation. An overall navigational accuracy of 90.9% and 71.43% were obtained respectively for the segment-based and object-based methods. These results also indicate how the two processes can function together in order to accomplish a navigational task in the absence of any external aid, as is the case with primates.
Performance Verification for Behavior-Based Robot Missions

(Georgia Institute of Technology, 2015-06) Lyons, Damian M. ; Arkin, Ronald C. ; Jiang, Shu ; Liu, Tsung-Ming ; Nirmal, Paramesh

Certain robot missions need to perform predictably in a physical environment that may have significant uncertainty. One approach is to leverage automatic software verification techniques to establish a performance guarantee. The addition of an environment model and uncertainty in both program and environment, however, means the state-space of a model-checking solution to the problem can be prohibitively large. An approach based on behavior-based controllers in a process-algebra framework that avoids state-space combinatorics is presented here. In this approach, verification of the robot program in the uncertain environment is reduced to a filtering problem for a Bayesian Network. Validation results are presented for the verification of a multiple-waypoint and an autonomous exploration robot mission.
Robotic Nudges: The Ethics of Engineering a More Socially Just Human Being

(Georgia Institute of Technology, 2015-03) Borenstein, Jason ; Arkin, Ronald C.

The time is nearing when robots are going to become a pervasive feature of our personal lives. They are already continuously operating in industrial, domestic, and military sectors. But a facet of their operation that has not quite reached its full potential is their involvement in our day-to-day routines as servants, caregivers, companions, and perhaps friends. It is clear that the multiple forms of robots already in existence and in the process of being designed will have a profound impact on human life. In fact, the motivation for their creation is largely shaped by their ability to do so. Encouraging patients to take medications, enabling children to socialize, and protecting the elderly from hazards within a living space is only a small sampling of how they could interact with humans. Their seemingly boundless potential stems in part from the possibility of their omnipresence but also because they can be physically instantiated, i.e., they are embodied in the real world, unlike many other devices. The extent of a robot’s influence on our lives hinges in large part on which design pathway the robot’s creator decides to pursue . The principal focus of this article is to generate discussion about the ethical acceptability of allowing designers to construct companion robots that nudge a user in a particular behavioral direction (and if so, under which circumstances). More specifically, we will delineate key issues related to the ethics of designing robots whose deliberate purpose is to nudge human users towards displaying greater concern for their fellow human beings, including by becoming more socially just. Important facets of this discussion include whether a robot’s “nudging ” behavior should occur with or without the user’s awareness and how much control the user should exert over it.
SLAM-Based Spatial Memory for Behavior-Based Robots

(Georgia Institute of Technology, 2015) Jiang, Shu ; Arkin, Ronald C.

Knowledge is essential for an autonomous robot to act intelligently when tasked with a mission. With recent leaps of progress, the paradigm of SLAM (Simultaneous Localization and Mapping) has emerged as an ideal source of spatial knowledge for autonomous robots. However, despite advancements in both paradigms of SLAM and robot control, research in the integration of these areas has been lacking and remained open to investigation. This paper presents an integration of SLAM into a behavior-based robotic system as a dynamically acquired spatial memory, which can be used to enable new behaviors and augment existing ones. The effectiveness of the integrated system is demonstrated with a biohazard search mission, where a robot is tasked to search and locate a biohazard within an unknown environment under a time constraint.
Using Visual Information for Spatial Advice-Giving in a Primate-Inspired Autonomous Robot

(Georgia Institute of Technology, 2015) Arkin, Ronald C. ; Velayudhan, Lakshmi ; Pettinati, Michael J.

This paper presents an approach to apply mental rotations in the context of robot navigation in support of spatial advice-giving. It describes the motivation in terms of cognitive processing, the underlying architecture, and robotic results.