Real-time recognition of human gestures for collaborative robots on assembly-line

International audienceWe present a framework and preliminary experimental results for real-time recognition of human operator actions. The goal is, for a collaborative industrial robot operating on same assembly-line as workers, to allow adaptation of its behavior and speed for smooth human-robot cooperation. To this end, it is necessary for the robot to monitor and understand behavior of humans around it. The real-time motion capture is performed using a "MoCap suit" of 12 inertial sensors estimating joint angles of upper-half of human body (neck, wrists, elbows, shoulders, etc...). In our experiment, we consider one particular assembly operation on car doors, which we have further subdivided into 4 successive steps: removing the adhesive protection from the waterproofing sheet, positioning the waterproofing sheet on the door, pre-sticking the sheet on the door, and finally installing the window "sealing strip". The gesture recognition is achieved continuously in real-time, using a technique combining an automatic time-rescaling similar to Dynamic Time Warp (DTW), and Hidden Markov Model (HMM) for estimating respective probabilities of the 4 learnt actions. Preliminary evaluation, conducted in real-world on an experimental assembly cell of car manufacturer PSA, shows a very promising action correct recognition rate of 96% on several repetitions of the same assembly operation by a single operator. Ongoing work aims at evaluating our framework for same actions recognition but on more executions by a larger pool of different human operators, and also to estimate false recognition rates on unrelated gestures. Another interesting potential perspective is the use of workers' motion capture in order to estimate effort and stress, for helping prevention of physical causes of some musculoskeletal disorders

Dedicated and industrial robotic arms used as force feedback telerobots at the AREVA-La Hague recycling plant

ISBN: 978-1-4244-6635-1/10International audienceCEA LIST and AREVA have been developing remote operations devices, also called telerobotics for 15 years. These tools were designed for interventions in the AREVA nuclear spent fuel facilities hot cells. From these 15 years of joint research and development, several technological bricks have been industrialized and used at the AREVA La Hague facilities. This article presents some of these bricks and their industrial developments. The “TAO2000” CEA LIST telerobotics generic software controller will be first discussed. This controller has been used to teleoperate dedicated slave arms like the MT200 TAO (an evolution of the conventional wall-transmission mechanical telemanipulator (MSM)) as well as industrial robotic arms like the Stäubli RX robots. Both the MT200 TAO and Stäubli RX TAO telerobotics systems provide force-feedback and are now ready to be used as telemaintenance tools at the AREVA La Hague facilities. Two recent maintenance operations using these tools will be detailed at the end of this pape

The Regulation, Governance and Ethics of Smart Robotic Systems in Manufacturing:UK and EU Insights

This White Paper—intended for policymakers, regulators, and other key stakeholders, such as employers, trade unions—outlines key regulatory, governance, and ethics considerations surrounding smart robotic systems aimed at the manufacturing sector. Drawing on the interdisciplinary research conducted within the UKRI Made Smarter Innovation-Research Centre for Smart, Collaborative Industrial Robotics (hereinafter referred to as ‘Smart Cobotics Centre’), this White Paper outlines existing frameworks for collaborative robots and smart robotic systems and provides recommendations for their reform to support safer and more effective adoption in manufacturing. While our primary focus is on the UK context, we also incorporate some comparative insights from the EU

The “Medical Exception” to Emotion Detection Algorithms within the EU's Forthcoming AI Act:Regulatory Implications for Therapeutical Smart Cobotics

The forthcoming AI Act prohibits emotion detection algorithms, except for medical and safety (chiefly interpretable as therapeutical) applications. This contribution discusses the implications of this exception for manufacturers and deployers of smart collaborative robotics in healthcare as well as general production settings. It delineates the boundaries of “therapy” for smart cobotic applications under EU law, and spotlights yet-unsolved quandaries for regulatory compliance

Market Structure analysis with Herfindahl-Hirchman Index and Lauraéus-Kaivo-oja Indices in the Global Cobotics Markets

Research purpose. The study is focused on the expected market dynamics of global cobotics markets. This study investigates the current market structure of the global cobotics market. The scientific aim of the research is to report the first data-based market structure analysis of the global cobotics market with the HHI index and with the LKI index analysis. With analysis we are able to show the diversification rate of the global cobotics market.Design / Methodology / Approach. The methodology is based on conventional statistical index theory and statistics. The methodology is the calculation of the Herfindahl-Hirchman Index and the Lauraéus-Kaivo-oja Index. The authors compare the results of these two methodologies.Findings. The Herfindahl-Hirschman Index (HHI) and the Lauraéus-Kaivo-oja Index are statistical measures of market concentration, and they can be used to determine market competitiveness. This paper demonstrates novel data analytics possibilities of new market data collected by the Statzon, Ltd with various comparative analytical results and findings. By our analyses we can help multiple industrial stakeholders make faster decisions and better strategic plans with the easiest and fastest access to accurate, reliable, and up-to-date cobotics industry statistics, forecasts, and insights. The finding is that this study reveals the current market structure of global cobotics. It is a novel finding and result.Originality / Value / Practical implications. This paper demonstrates the novel and exciting possibilities of transparent index calculation tools. The authors provide original results. Authors underline that extra value added to stakeholders and customers will be provided by joint data pooling strategy of various data sources, which is a key approach of this paper. Real-time market structure analyses create reliable and knowledge-based information for decision-makers and stakeholders of the global cobotics industry.KeywordsMarket trendsMarket structure of global cobotics marketHerfindahl-Hirschman Index (HHI)Lauraéus-Kaivo-oja Index (LKI)Market data analyticsJEL ClassificationC13C53C63D52G28</ul

Language-free graphical signage improves human performance and reduces anxiety when working collaboratively with robots

As robots become more ubiquitous, and their capabilities extend, novice users will require intuitive instructional information related to their use. This is particularly important in the manufacturing sector, which is set to be transformed under Industry 4.0 by the deployment of collaborative robots in support of traditionally low-skilled, manual roles. In the first study of its kind, this paper reports how static graphical signage can improve performance and reduce anxiety in participants physically collaborating with a semi-autonomous robot. Three groups of 30 participants collaborated with a robot to perform a manufacturing-type process using graphical information that was relevant to the task, irrelevant, or absent. The results reveal that the group exposed to relevant signage was significantly more accurate in undertaking the task. Furthermore, their anxiety towards robots significantly decreased as a function of increasing accuracy. Finally, participants exposed to graphical signage showed positive emotional valence in response to successful trials. At a time when workers are concerned about the threat posed by robots to jobs, and with advances in technology requiring upskilling of the workforce, it is important to provide intuitive and supportive information to users. Whilst increasingly sophisticated technical solutions are being sought to improve communication and confidence in human-robot co-working, our findings demonstrate how simple signage can still be used as an effective tool to reduce user anxiety and increase task performance

Comparative Study Of Robotic And Manual Welding For Energy Consumption And Efficiency In A High Mix, Low Volume Manufacturing Environment

This study examines the comparative efficiency and energy consumption of manual versus robotic welding in high-mix, low-volume (HMLV) manufacturing environments. Traditional robotic welding systems have been predominantly used in low-mix, high-volume production due to their efficiency in repetitive tasks. However, the advent of collaborative robots (cobots) has democratized robotic automation for diverse manufacturing needs. Cobots allow flexibility in programming, enabling their deployment in HMLV environments characterized by hard product variety and smaller batch sizes. This research evaluates energy consumption, welding speed, and quality metrics across manual and cobotic welding systems. Data were gathered using energy meters and video analysis, focusing on weld geometries, part complexities, and production contexts. The cobotic weldments proved to be 13.5% - 37% stronger for all parts and configurations, and energy consumptions was reduced by 41% – 71% in single-sided applications. This allowed for the development of equations to predict the cycle time and energy consumption of complex weldments. The use of cobots reduced the cycle time by 39% for these parts. The findings establish guidelines for optimizing robotic welding implementation, ensuring energy efficiency without compromising productivity or weld quality. The study contributes a decision-making framework to assess the viability of robotic welding adoption, balancing economic and environmental considerations in modern manufacturing

Cobotic service teams and power dynamics:Understanding and mitigating unintended consequences of human-robot collaboration in healthcare services

In cobotic service teams, employees and robots collaborate to serve customers. As cobotic teams become more prevalent, a key question arises: How do consumers respond to cobotic teams, as a function of the roles shared by employees and robots (robots in superordinate roles as team leaders and humans in subordinate roles as assistants, or vice versa)? Six studies, conducted in different healthcare settings, show that consumers respond less favorably to robot-led (vs. human-led) teams. In delineating the process underlying these responses, the authors demonstrate that consumers ascribe less power to robot (vs. human) team leaders, which increases consumer anxiety and drives downstream responses through serial mediation. Further examining the power dynamics in cobotic service encounters, the authors identify boundary conditions that help mitigate negative consumer responses (increasing consumers’ power by letting them choose the robot in the service team, leveraging consumers’ power distance beliefs, and reinforcing the robot’s performance capabilities).</p

Viva robonomics!? Cost–benefit analysis of robots and future directions in service and robonomics research

Purpose: Despite extensive research on the design and adoption of service robots, their efficiency—specifically, the impact on costs, revenues and profitability—has received limited attention. This essay seeks to stimulate a scholarly conversation on this topic by surveying the emerging literature on empirical insights on cost–benefit analyses and then highlighting key components of cost-benefit analyses for service robots. Next, grounded in “service profit logic,” this essay empirically examines consumer willingness-to-pay (WTP) vis-à-vis human-robot (cobotic) teams as a crucial marketing variable in the context of cost–benefit analyses for service robots. Design/methodology/approach: This research combines a review of empirical findings from the literature on cost–benefit analysis and consumer WTP in the context of service robots with the first exploratory experimental study investigating consumer WTP for a cobotic service team. Findings: This essay offers an illustrative process for cost–benefit analyses of service robots, outlining key cost drivers and benefits and reviewing empirical evidence. The findings highlight the situational profitability of robots, with economic feasibility influenced by context and usage frequency. Consumer WTP is shaped, among others, by perceived usefulness, emotional engagement and anthropomorphic features of service robots. An exploratory study on cobotic teams in healthcare reveals they can increase WTP for human-only teams, especially when robots are in leadership roles. The essay concludes with proposed directions for future research. Originality/value: Building on existing literature, this essay expands the understanding of cost–benefit analysis of service robots. Further, it offers novel initial empirical insights into consumer WTP for cobotic service teams.</p

Two Suns? The Algorithmic State: History and Theory

What follows is a history of cultural blindness. We might need to consider our historiography, the culture we find in the past, if you like, and the need to now reconstitute and re-frame that sense of history making the development of robotics and machine learning more central. Over in a usually forgotten corner there is a history of machines that may throw light on where we find ourselves today and in this section there is a consideration of that history, a story about robotics and theorists in this area unheard and unseen in many respects