Monthly Archives: September 2021

You are browsing the site archives by month.

A model of the psychomotor behaviour of humans intended to be useful for integration with robots

September 3, 2021 11:14 ,

Stephen Fox, Adrian Kotelba, Ilari Marstio, Jari Montonen, Aligning human psychomotor characteristics with robots, exoskeletons and augmented reality, Robotics and Computer-Integrated Manufacturing, Volume 63, 2020, DOI: 10.1016/j.rcim.2019.101922.

In previous production literature, the uncertainty of human behaviour has been recognized as a source of productivity, quality, and safety problems. However, fundamental reasons for the uncertainty of human behavior have received little analysis in the production literature. Furthermore, potential for these fundamental reasons to be aligned with production technologies in order to improve production performance has not been addressed. By contrast, in this paper, fundamental reasons for the uncertainty of human behaviour are explained through a model of psychomotor characteristics that encompasses physiology, past experiences, personality, gender, culture, emotion, reasoning, and biocybernetics. Through reference to 10 action research cases, the formal model is applied to provide guidelines for planning production work that includes robots, exoskeletons, and augmented reality.

Posted in: Human-robot interaction, Psycho-physiological bases of engineering , Tagged:

State of the art in standards for Robotics

September 3, 2021 11:10 ,

Z.M. Bi, Zhonghua Miao, Bin Zhang, Chris W.J. Zhang, The state of the art of testing standards for integrated robotic systems, Robotics and Computer-Integrated Manufacturing
Volume 63, June 2020, DOI: 10.1016/j.rcim.2019.101893.

Technology standards facilitate the transparency in market and the supplies of products with good quality. For manufacturers, standards make it possible to reduce the costs by mass production, and enhance system adaptabilities through integrating system modules with the standardized interfaces. However, International standards on industrial robots such as ISO-9283 were developed in 1998, and they have not updated since then. Due to every-increasing applications of robots in complex systems, there is an emerging need to advance existing standards on robots for a broader scope of system components and system integration. This paper gives an introduction of the endeavors by National Institute of Standards and Technology (NIST); especially, it overviews the recent progresses on the standardized tests of robotic systems and components. The presented work aims to identify the limitations of existing industrial standards and clarify the trend of technology standardizations for industrial robotic systems.

Posted in: Industrial robots , Tagged:

Symbol grounding through neural networks

September 3, 2021 11:06 ,

Shridhar M, Mittal D, Hsu D., INGRESS: Interactive visual grounding of referring expressions, The International Journal of Robotics Research. January 2020, DOI: 10.1177/0278364919897133.

This article presents INGRESS, a robot system that follows human natural language instructions to pick and place everyday objects. The key question here is to ground referring expressions: understand expressions about objects and their relationships from image and natural language inputs. INGRESS allows unconstrained object categories and rich language expressions. Further, it asks questions to clarify ambiguous referring expressions interactively. To achieve these, we take the approach of grounding by generation and propose a two-stage neural-network model for grounding. The first stage uses a neural network to generate visual descriptions of objects, compares them with the input language expressions, and identifies a set of candidate objects. The second stage uses another neural network to examine all pairwise relations between the candidates and infers the most likely referred objects. The same neural networks are used for both grounding and question generation for disambiguation. Experiments show that INGRESS outperformed a state-of-the-art method on the RefCOCO dataset and in robot experiments with humans. The INGRESS source code is available at https://github.com/MohitShridhar/ingress.

Posted in: Human-robot interaction, Psycho-physiological bases of engineering , Tagged:

Adapting perception to environmental changes explicitly

September 3, 2021 11:02 ,

Sriram Siva, Hao Zhang, Robot perceptual adaptation to environment changes for long-term human teammate following, The International Journal of Robotics Research. January 2020, DOI: 10.1177/0278364919896625.

Perception is one of the several fundamental abilities required by robots, and it also poses significant challenges, especially in real-world field applications. Long-term autonomy introduces additional difficulties to robot perception, including short- and long-term changes of the robot operation environment (e.g., lighting changes). In this article, we propose an innovative human-inspired approach named robot perceptual adaptation (ROPA) that is able to calibrate perception according to the environment context, which enables perceptual adaptation in response to environmental variations. ROPA jointly performs feature learning, sensor fusion, and perception calibration under a unified regularized optimization framework. We also implement a new algorithm to solve the formulated optimization problem, which has a theoretical guarantee to converge to the optimal solution. In addition, we collect a large-scale dataset from physical robots in the field, called perceptual adaptation to environment changes (PEAC), with the aim to benchmark methods for robot adaptation to short-term and long-term, and fast and gradual lighting changes for human detection based upon different feature modalities extracted from color and depth sensors. Utilizing the PEAC dataset, we conduct extensive experiments in the application of human recognition and following in various scenarios to evaluate ROPA. Experimental results have validated that the ROPA approach obtains promising performance in terms of accuracy and efficiency, and effectively adapts robot perception to address short-term and long-term lighting changes in human detection and following applications.

Posted in: Robot sensors , Tagged: