James Kramer

Bio: James Kramer is an academic researcher from University of Notre Dame. The author has contributed to research in topics: Human–robot interaction & Social robot. The author has an hindex of 7, co-authored 12 publications receiving 633 citations.

Development environments for autonomous mobile robots: A survey

Abstract: Robotic Development Environments (RDEs) have come to play an increasingly important role in robotics research in general, and for the development of architectures for mobile robots in particular. Yet, no systematic evaluation of available RDEs has been performed; establishing a comprehensive list of evaluation criteria targeted at robotics applications is desirable that can subsequently be used to compare their strengths and weaknesses. Moreover, there are no practical evaluations of the usability and impact of a large selection of RDEs that provides researchers with the information necessary to select an RDE most suited to their needs, nor identifies trends in RDE research that suggest directions for future RDE development. This survey addresses the above by selecting and describing nine open source, freely available RDEs for mobile robots, evaluating and comparing them from various points of view. First, based on previous work concerning agent systems, a conceptual framework of four broad categories is established, encompassing the characteristics and capabilities that an RDE supports. Then, a practical evaluation of RDE usability in designing, implementing, and executing robot architectures is presented. Finally, the impact of specific RDEs on the field of robotics is addressed by providing a list of published applications and research projects that give concrete examples of areas in which systems have been used. The comprehensive evaluation and comparison of the nine RDEs concludes with suggestions of how to use the results of this survey and a brief discussion of future trends in RDE design.

First steps toward natural human-like HRI

Abstract: Natural human-like human-robot interaction (NHL-HRI) requires the robot to be skilled both at recognizing and producing many subtle human behaviors, often taken for granted by humans. We suggest a rough division of these requirements for NHL-HRI into three classes of properties: (1) social behaviors, (2) goal-oriented cognition, and (3) robust intelligence, and present the novel DIARC architecture for complex affective robots for human-robot interaction, which aims to meet some of those requirements. We briefly describe the functional properties of DIARC and its implementation in our ADE system. Then we report results from human subject evaluations in the laboratory as well as our experiences with the robot running ADE at the 2005 AAAI Robot Competition in the Open Interaction Event and Robot Exhibition.

The utility of affect expression in natural language interactions in joint human-robot tasks

Abstract: Recognizing and responding to human affect is important in collaborative tasks in joint human-robot teams. In this paper we present an integrated affect and cognition architecture for HRI and report results from an experiment with this architecture that shows that expressing affect and responding to human affect with affect expressions can significantly improve team performance in a joint human-robot task.

DIARC: a testbed for natural human-robot interaction

Abstract: DIARC, a distributed integrated affect, reflection, cognition architecture for robots, provides many features that are critical to successful natural human-robot interaction As such, DIARC is an ideal platform for experimentation in HRI In this paper we describe the architecture and and its implementation in ADE, paying particular attention to its interaction capabilities and features that allow robust operation These features are evaluated in the context of the 2006 AAAI Robot Competition

Reflection and Reasoning Mechanisms for Failure Detection and Recovery in a Distributed Robotic Architecture for Complex Robots

Abstract: Complex robots that interact naturally with humans require the integration, coordination and maintenance of many diverse software components and algorithms. An architecture that incorporates explicit knowledge about the relationships among these components and the overall system state can be used for introspection and consequently to reason about the best configurations of the computing environment under changing conditions; potential uses include maintaining the system's integrity, promoting its health, and providing the ability to dynamically reconfigure system components (e.g., after component failure). In this paper, we describe a rudimentary reasoning system, part of our distributed integrated affect reflection cognition (DIARC) architecture for human-robot interaction, that can autonomously perform failure detection, failure recovery, and system reconfiguration of distributed architectural components to ensure sustained operation and interactions. We demonstrate the functionality and utility of the proposed mechanisms on a robot, where architectural components are forcefully removed by hand and automatically recovered by the system while the robot is continuing its interactions with humans as part of a joint human-robot task.

ROS: an open-source Robot Operating System

Abstract: This paper gives an overview of ROS, an opensource robot operating system. ROS is not an operating system in the traditional sense of process management and scheduling; rather, it provides a structured communications layer above the host operating systems of a heterogenous compute cluster. In this paper, we discuss how ROS relates to existing robot software frameworks, and briefly overview some of the available application software which uses ROS.

Swarm robotics: a review from the swarm engineering perspective

Abstract: Swarm robotics is an approach to collective robotics that takes inspiration from the self-organized behaviors of social animals. Through simple rules and local interactions, swarm robotics aims at designing robust, scalable, and flexible collective behaviors for the coordination of large numbers of robots. In this paper, we analyze the literature from the point of view of swarm engineering: we focus mainly on ideas and concepts that contribute to the advancement of swarm robotics as an engineering field and that could be relevant to tackle real-world applications. Swarm engineering is an emerging discipline that aims at defining systematic and well founded procedures for modeling, designing, realizing, verifying, validating, operating, and maintaining a swarm robotics system. We propose two taxonomies: in the first taxonomy, we classify works that deal with design and analysis methods; in the second taxonomy, we classify works according to the collective behavior studied. We conclude with a discussion of the current limits of swarm robotics as an engineering discipline and with suggestions for future research directions.

Intuitive computing methods and systems

Abstract: A smart phone senses audio, imagery, and/or other stimulus from a user's environment, and acts autonomously to fulfill inferred or anticipated user desires. In one aspect, the detailed technology concerns phone-based cognition of a scene viewed by the phone's camera. The image processing tasks applied to the scene can be selected from among various alternatives by reference to resource costs, resource constraints, other stimulus information (e.g., audio), task substitutability, etc. The phone can apply more or less resources to an image processing task depending on how successfully the task is proceeding, or based on the user's apparent interest in the task. In some arrangements, data may be referred to the cloud for analysis, or for gleaning. Cognition, and identification of appropriate device response(s), can be aided by collateral information, such as context. A great number of other features and arrangements are also detailed.

ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems

Abstract: We present a novel multi-robot simulator named ARGoS. ARGoS is designed to simulate complex experiments involving large swarms of robots of different types. ARGoS is the first multi-robot simulator that is at the same time both efficient (fast performance with many robots) and flexible (highly customizable for specific experiments). Novel design choices in ARGoS have enabled this breakthrough. First, in ARGoS, it is possible to partition the simulated space into multiple sub-spaces, managed by different physics engines running in parallel. Second, ARGoS’ architecture is multi-threaded, thus designed to optimize the usage of modern multi-core CPUs. Finally, the architecture of ARGoS is highly modular, enabling easy addition of custom features and appropriate allocation of computational resources. We assess the efficiency of ARGoS and showcase its flexibility with targeted experiments. Experimental results demonstrate that simulation run-time increases linearly with the number of robots. A 2D-dynamics simulation of 10,000 e-puck robots can be performed in 60 % of the time taken by the corresponding real-world experiment. We show how ARGoS can be extended to suit the needs of an experiment in which custom functionality is necessary to achieve sufficient simulation accuracy. ARGoS is open source software licensed under GPL3 and is downloadable free of charge.

Massively multi-robot simulation in stage

Abstract: Stage is a C++ software library that simulates multiple mobile robots. Stage version 2, as the simulation backend for the Player/Stage system, may be the most commonly used robot simulator in research and university teaching today. Development of Stage version 3 has focused on improving scalability, usability, and portability. This paper examines Stage’s scalability.