skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Web Perspectives in Robotics Applications: Commonsense Knowledge, Autonomous Vehicles and Human-Robot Collaboration
The realms of commonsense knowledge and reasoning, vehicle automation with full as well as partial autonomy, and human-robot collaboration, present growing areas of research in recent times, with much of the concerned data being disseminated through the Web and devices encompassing IoT (Internet of Things); the data per se being heterogeneous including plain text, images, audiovisuals, hypertext and hypermedia. Due to the advent of autonomous vehicles, there is a greater need for the embodiment of commonsense knowledge within their development in order to simulate subtle, intuitive aspects of human judgment. The field of robotics has often encountered collaborative tasks between humans and robots to enhance the respective activities involved and produce better results than humans or robots would achieve working by themselves. Accordingly, this article outlines and organizes some of the research occurring in these areas along with its Web perspectives and applications. Context related to human-robot collaboration and commonsense knowledge appears via a survey of the literature. Vehicle automation is significant with the relevant studies: its definition and methods of improvement are of focus in the article. Some work in this area makes an impact on smart manufacturing. There is discussion on how human-robot collaboration is beneficial, and how commonsense knowledge is useful for the collaboration to occur in an enhanced manner. This article would be potentially interesting to various communities, e.g. AI professionals, Web developers, robotics engineers, and data scientists.  more » « less
Award ID(s):
2117308
PAR ID:
10451714
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
ACM SIGWEB Newsletter
Volume:
2023
Issue:
Winter
ISSN:
1931-1745
Page Range / eLocation ID:
1 to 22
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Regular inspection and monitoring of buildings and infrastructure, that is collectively called the built environment in this paper, is critical. The built environment includes commercial and residential buildings, roads, bridges, tunnels, and pipelines. Automation and robotics can aid in reducing errors and increasing the efficiency of inspection tasks. As a result, robotic inspection and monitoring of the built environment has become a significant research topic in recent years. This review paper presents an in-depth qualitative content analysis of 269 papers on the use of robots for the inspection and monitoring of buildings and infrastructure. The review found nine different types of robotic systems, with unmanned aerial vehicles (UAVs) being the most common, followed by unmanned ground vehicles (UGVs). The study also found five different applications of robots in inspection and monitoring, namely, maintenance inspection, construction quality inspection, construction progress monitoring, as-built modeling, and safety inspection. Common research areas investigated by researchers include autonomous navigation, knowledge extraction, motion control systems, sensing, multi-robot collaboration, safety implications, and data transmission. The findings of this study provide insight into the recent research and developments in the field of robotic inspection and monitoring of the built environment and will benefit researchers, and construction and facility managers, in developing and implementing new robotic solutions. 
    more » « less
  2. Abstract Robotic automation in construction has created the need for new competencies that will enable the workforce to engage with robots safely and effectively. However, differing perceptions between industry professionals and academia make aligning academic programs with industry needs challenging. This study evaluates these perceptions to guide the design of HRC training programs. A three-round Delphi study was conducted separately with panels of industry professionals and academic experts to assess their views on HRC competencies in construction. The findings revealed that both panels identified human–robot interfaces, HRC safety and standards, robot control systems, and construction robot applications as the top five HRC knowledge areas. Industry professionals also emphasized task planning knowledge, while academic experts focused on HRC ethics. Key HRC skills include effective communication, safety management, technical proficiency, and compliance with regulations and standards, with industry professionals prioritizing proficiency in task planning and academics emphasizing human–robot interface proficiency. Both expert panels prioritized teamwork, continuous learning, problem-solving, communication, and adaptability as top-rated HRC abilities. This study contributes to knowledge by defining key HRC competencies and identifying differences in priorities between industry and academia. These insights can guide the development of academic curricula that better align with industry needs, supporting the creation of training programs that equip the workforce with the competencies required for safe and effective robotic collaboration. The study also promotes collaboration between industry and academia, fostering innovation in HRC and robotics in construction. Future research directions are proposed to explore innovative training methods to equip the future workforce with HRC competencies. 
    more » « less
  3. Abstract Effective interactions between humans and robots are vital to achieving shared tasks in collaborative processes. Robots can utilize diverse communication channels to interact with humans, such as hearing, speech, sight, touch, and learning. Our focus, amidst the various means of interactions between humans and robots, is on three emerging frontiers that significantly impact the future directions of human–robot interaction (HRI): (i) human–robot collaboration inspired by human–human collaboration, (ii) brain-computer interfaces, and (iii) emotional intelligent perception. First, we explore advanced techniques for human–robot collaboration, covering a range of methods from compliance and performance-based approaches to synergistic and learning-based strategies, including learning from demonstration, active learning, and learning from complex tasks. Then, we examine innovative uses of brain-computer interfaces for enhancing HRI, with a focus on applications in rehabilitation, communication, brain state and emotion recognition. Finally, we investigate the emotional intelligence in robotics, focusing on translating human emotions to robots via facial expressions, body gestures, and eye-tracking for fluid, natural interactions. Recent developments in these emerging frontiers and their impact on HRI were detailed and discussed. We highlight contemporary trends and emerging advancements in the field. Ultimately, this paper underscores the necessity of a multimodal approach in developing systems capable of adaptive behavior and effective interaction between humans and robots, thus offering a thorough understanding of the diverse modalities essential for maximizing the potential of HRI. 
    more » « less
  4. Abstract Robotics researchers have been focusing on developing autonomous and human-like intelligent robots that are able to plan, navigate, manipulate objects, and interact with humans in both static and dynamic environments. These capabilities, however, are usually developed for direct interactions with people in controlled environments, and evaluated primarily in terms of human safety. Consequently, human-robot interaction (HRI) in scenarios with no intervention of technical personnel is under-explored. However, in the future, robots will be deployed in unstructured and unsupervised environments where they will be expected to work unsupervised on tasks which require direct interaction with humans and may not necessarily be collaborative. Developing such robots requires comparing the effectiveness and efficiency of similar design approaches and techniques. Yet, issues regarding the reproducibility of results, comparing different approaches between research groups, and creating challenging milestones to measure performance and development over time make this difficult. Here we discuss the international robotics competition called RoboCup as a benchmark for the progress and open challenges in AI and robotics development. The long term goal of RoboCup is developing a robot soccer team that can win against the world’s best human soccer team by 2050. We selected RoboCup because it requires robots to be able to play with and against humans in unstructured environments, such as uneven fields and natural lighting conditions, and it challenges the known accepted dynamics in HRI. Considering the current state of robotics technology, RoboCup’s goal opens up several open research questions to be addressed by roboticists. In this paper, we (a) summarise the current challenges in robotics by using RoboCup development as an evaluation metric, (b) discuss the state-of-the-art approaches to these challenges and how they currently apply to RoboCup, and (c) present a path for future development in the given areas to meet RoboCup’s goal of having robots play soccer against and with humans by 2050. 
    more » « less
  5. An important component for the effective collaboration of humans with robots is the compatibility of their movements, especially when humans physically collaborate with a robot partner. Following previous findings that humans interact more seamlessly with a robot that moves with humanlike or biological velocity profiles, this study examined whether humans can adapt to a robot that violates human signatures. The specific focus was on the role of extensive practice and realtime augmented feedback. Six groups of participants physically tracked a robot tracing an ellipse with profiles where velocity scaled with the curvature of the path in biological and nonbiological ways, while instructed to minimize the interaction force with the robot. Three of the 6 groups received real-time visual feedback about their force error. Results showed that with 3 daily practice sessions, when given feedback about their force errors, humans could decrease their interaction forces when the robot’s trajectory violated human-like velocity patterns. Conversely, when augmented feedback was not provided, there were no improvements despite this extensive practice. The biological profile showed no improvements, even with feedback, indicating that the (non-zero) force had already reached a floor level. These findings highlight the importance of biological robot trajectories and augmented feedback to guide humans to adapt to non-biological movements in physical human-robot interaction. These results have implications on various fields of robotics, such as surgical applications and collaborative robots for industry. 
    more » « less