9,242 research outputs found
Human-Robot Interaction using VAHR: Virtual Assistant, Human, and Robots in the Loop
Robots have become ubiquitous tools in various industries and households,
highlighting the importance of human-robot interaction (HRI). This has
increased the need for easy and accessible communication between humans and
robots. Recent research has focused on the intersection of virtual assistant
technology, such as Amazon's Alexa, with robots and its effect on HRI. This
paper presents the Virtual Assistant, Human, and Robots in the loop (VAHR)
system, which utilizes bidirectional communication to control multiple robots
through Alexa. VAHR's performance was evaluated through a human-subjects
experiment, comparing objective and subjective metrics of traditional keyboard
and mouse interfaces to VAHR. The results showed that VAHR required 41% less
Robot Attention Demand and ensured 91% more Fan-out time compared to the
standard method. Additionally, VAHR led to a 62.5% improvement in
multi-tasking, highlighting the potential for efficient human-robot interaction
in physically- and mentally-demanding scenarios. However, subjective metrics
revealed a need for human operators to build confidence and trust with this new
method of operation.Comment: 7 pages, 7 figure
Towards Autonomous Selective Harvesting: A Review of Robot Perception, Robot Design, Motion Planning and Control
This paper provides an overview of the current state-of-the-art in selective
harvesting robots (SHRs) and their potential for addressing the challenges of
global food production. SHRs have the potential to increase productivity,
reduce labour costs, and minimise food waste by selectively harvesting only
ripe fruits and vegetables. The paper discusses the main components of SHRs,
including perception, grasping, cutting, motion planning, and control. It also
highlights the challenges in developing SHR technologies, particularly in the
areas of robot design, motion planning and control. The paper also discusses
the potential benefits of integrating AI and soft robots and data-driven
methods to enhance the performance and robustness of SHR systems. Finally, the
paper identifies several open research questions in the field and highlights
the need for further research and development efforts to advance SHR
technologies to meet the challenges of global food production. Overall, this
paper provides a starting point for researchers and practitioners interested in
developing SHRs and highlights the need for more research in this field.Comment: Preprint: to be appeared in Journal of Field Robotic
The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions
The Metaverse offers a second world beyond reality, where boundaries are
non-existent, and possibilities are endless through engagement and immersive
experiences using the virtual reality (VR) technology. Many disciplines can
benefit from the advancement of the Metaverse when accurately developed,
including the fields of technology, gaming, education, art, and culture.
Nevertheless, developing the Metaverse environment to its full potential is an
ambiguous task that needs proper guidance and directions. Existing surveys on
the Metaverse focus only on a specific aspect and discipline of the Metaverse
and lack a holistic view of the entire process. To this end, a more holistic,
multi-disciplinary, in-depth, and academic and industry-oriented review is
required to provide a thorough study of the Metaverse development pipeline. To
address these issues, we present in this survey a novel multi-layered pipeline
ecosystem composed of (1) the Metaverse computing, networking, communications
and hardware infrastructure, (2) environment digitization, and (3) user
interactions. For every layer, we discuss the components that detail the steps
of its development. Also, for each of these components, we examine the impact
of a set of enabling technologies and empowering domains (e.g., Artificial
Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on
its advancement. In addition, we explain the importance of these technologies
to support decentralization, interoperability, user experiences, interactions,
and monetization. Our presented study highlights the existing challenges for
each component, followed by research directions and potential solutions. To the
best of our knowledge, this survey is the most comprehensive and allows users,
scholars, and entrepreneurs to get an in-depth understanding of the Metaverse
ecosystem to find their opportunities and potentials for contribution
ENABLING EFFICIENT FLEET COMPOSITION SELECTION THROUGH THE DEVELOPMENT OF A RANK HEURISTIC FOR A BRANCH AND BOUND METHOD
In the foreseeable future, autonomous mobile robots (AMRs) will become a key enabler
for increasing productivity and flexibility in material handling in warehousing facilities,
distribution centers and manufacturing systems.
The objective of this research is to develop and validate parametric models of AMRs,
develop ranking heuristic using a physics-based algorithm within the framework of the
Branch and Bound method, integrate the ranking algorithm into a Fleet Composition
Optimization (FCO) tool, and finally conduct simulations under various scenarios to
verify the suitability and robustness of the developed tool in a factory equipped with
AMRs. Kinematic-based equations are used for computing both energy and time
consumption. Multivariate linear regression, a data-driven method, is used for designing
the ranking heuristic. The results indicate that the unique physical structures and
parameters of each robot are the main factors contributing to differences in energy and
time consumption. improvement on reducing computation time was achieved by
comparing heuristic-based search and non-heuristic-based search. This research is
expected to significantly improve the current nested fleet composition optimization tool
by reducing computation time without sacrificing optimality. From a practical
perspective, greater efficiency in reducing energy and time costs can be achieved.Ford Motor CompanyNo embargoAcademic Major: Aerospace Engineerin
A Design Science Research Approach to Smart and Collaborative Urban Supply Networks
Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness.
A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense.
Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice
Corporate Social Responsibility: the institutionalization of ESG
Understanding the impact of Corporate Social Responsibility (CSR) on firm performance as it relates to industries reliant on technological innovation is a complex and perpetually evolving challenge. To thoroughly investigate this topic, this dissertation will adopt an economics-based structure to address three primary hypotheses. This structure allows for each hypothesis to essentially be a standalone empirical paper, unified by an overall analysis of the nature of impact that ESG has on firm performance. The first hypothesis explores the evolution of CSR to the modern quantified iteration of ESG has led to the institutionalization and standardization of the CSR concept. The second hypothesis fills gaps in existing literature testing the relationship between firm performance and ESG by finding that the relationship is significantly positive in long-term, strategic metrics (ROA and ROIC) and that there is no correlation in short-term metrics (ROE and ROS). Finally, the third hypothesis states that if a firm has a long-term strategic ESG plan, as proxied by the publication of CSR reports, then it is more resilience to damage from controversies. This is supported by the finding that pro-ESG firms consistently fared better than their counterparts in both financial and ESG performance, even in the event of a controversy. However, firms with consistent reporting are also held to a higher standard than their nonreporting peers, suggesting a higher risk and higher reward dynamic. These findings support the theory of good management, in that long-term strategic planning is both immediately economically beneficial and serves as a means of risk management and social impact mitigation. Overall, this contributes to the literature by fillings gaps in the nature of impact that ESG has on firm performance, particularly from a management perspective
Towards Reuse and Recycling of Lithium-ion Batteries: Tele-robotics for Disassembly of Electric Vehicle Batteries
Disassembly of electric vehicle batteries is a critical stage in recovery,
recycling and re-use of high-value battery materials, but is complicated by
limited standardisation, design complexity, compounded by uncertainty and
safety issues from varying end-of-life condition. Telerobotics presents an
avenue for semi-autonomous robotic disassembly that addresses these challenges.
However, it is suggested that quality and realism of the user's haptic
interactions with the environment is important for precise, contact-rich and
safety-critical tasks. To investigate this proposition, we demonstrate the
disassembly of a Nissan Leaf 2011 module stack as a basis for a comparative
study between a traditional asymmetric haptic-'cobot' master-slave framework
and identical master and slave cobots based on task completion time and success
rate metrics. We demonstrate across a range of disassembly tasks a time
reduction of 22%-57% is achieved using identical cobots, yet this improvement
arises chiefly from an expanded workspace and 1:1 positional mapping, and
suffers a 10-30% reduction in first attempt success rate. For unbolting and
grasping, the realism of force feedback was comparatively less important than
directional information encoded in the interaction, however, 1:1 force mapping
strengthened environmental tactile cues for vacuum pick-and-place and contact
cutting tasks.Comment: 21 pages, 12 figures, Submitted to Frontiers in Robotics and AI;
Human-Robot Interactio
The place where curses are manufactured : four poets of the Vietnam War
The Vietnam War was unique among American wars. To pinpoint its uniqueness, it was necessary to look for a non-American voice that would enable me to articulate its distinctiveness and explore the American character as observed by an Asian. Takeshi Kaiko proved to be most helpful. From his novel, Into a Black Sun, I was able to establish a working pair of 'bookends' from which to approach the poetry of Walter McDonald, Bruce Weigl, Basil T. Paquet and Steve Mason. Chapter One is devoted to those seemingly mismatched 'bookends,' Walt Whitman and General William C. Westmoreland, and their respective anthropocentric and technocentric visions of progress and the peculiarly American concept of the "open road" as they manifest themselves in Vietnam. In Chapter, Two, I analyze the war poems of Walter McDonald. As a pilot, writing primarily about flying, his poetry manifests General Westmoreland's technocentric vision of the 'road' as determined by and manifest through technology. Chapter Three focuses on the poems of Bruce Weigl. The poems analyzed portray the literal and metaphorical descent from the technocentric, 'numbed' distance of aerial warfare to the world of ground warfare, and the initiation of a 'fucking new guy,' who discovers the contours of the self's interior through a set of experiences that lead from from aerial insertion into the jungle to the degradation of burning human
feces. Chapter Four, devoted to the thirteen poems of Basil T. Paquet, focuses on the continuation of the descent begun in Chapter Two. In his capacity as a medic, Paquet's entire body of poems details his quotidian tasks which entail tending the maimed, the mortally wounded and the dead. The final chapter deals with Steve Mason's JohnnY's Song, and his depiction of the plight of Vietnam veterans back in "The World" who are still trapped inside the interior landscape of their individual "ghettoes" of the soul created by their war-time experiences
Strategies for Early Learners
Welcome to learning about how to effectively plan curriculum for young children. This textbook will address: • Developing curriculum through the planning cycle • Theories that inform what we know about how children learn and the best ways for teachers to support learning • The three components of developmentally appropriate practice • Importance and value of play and intentional teaching • Different models of curriculum • Process of lesson planning (documenting planned experiences for children) • Physical, temporal, and social environments that set the stage for children’s learning • Appropriate guidance techniques to support children’s behaviors as the self-regulation abilities mature. • Planning for preschool-aged children in specific domains including o Physical development o Language and literacy o Math o Science o Creative (the visual and performing arts) o Diversity (social science and history) o Health and safety • Making children’s learning visible through documentation and assessmenthttps://scholar.utc.edu/open-textbooks/1001/thumbnail.jp
A reinforcement learning approach for transaction scheduling in a shuttle-based storage and retrieval system
With recent Industry 4.0 developments, companies tend to automate their industries. Warehousing companies also take part in this trend. A shuttle-based storage and retrieval system (SBS/RS) is an automated storage and retrieval system technology experiencing recent drastic market growth. This technology is mostly utilized in large distribution centers processing mini-loads. With the recent increase in e-commerce practices, fast delivery requirements with low volume orders have increased. SBS/RS provides ultrahigh-speed load handling due to having an excess amount of shuttles in the system. However, not only the physical design of an automated warehousing technology but also the design of operational system policies would help with fast handling targets. In this work, in an effort to increase the performance of an SBS/RS, we apply a machine learning (ML) (i.e., Q-learning) approach on a newly proposed tier-to-tier SBS/RS design, redesigned from a traditional tier-captive SBS/RS. The novelty of this paper is twofold: First, we propose a novel SBS/RS design where shuttles can travel between tiers in the system; second, due to the complexity of operation of shuttles in that newly proposed design, we implement an ML-based algorithm for transaction selection in that system. The ML-based solution is compared with traditional scheduling approaches: first-in-first-out and shortest process time (i.e., travel) scheduling rules. The results indicate that in most cases, the Q-learning approach performs better than the two static scheduling approaches
- …