IKR – Institut für angewandte Künstliche Intelligenz und Robotik
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Following the recent breakthrough of generative artificial intelligence, humanoid robots have shown significant developments within recent years. Unlike traditional robotics and automation solutions, humanoid robots promise increased flexibility. This development has positioned them as a possible solution to fill the automation gap between large companies and many small and medium-sized enterprises (SMEs), as caused by small batch sizes. This study aims to evaluate the application potential of humanoid robots for SMEs via a qualitative research approach. Within this study, six experts were interviewed based on six categories and hypotheses derived from an extensive literature review. Their responses were systematically analyzed via a qualitative content analysis. The results of this study have shown a large application potential for simple logistics and manufacturing tasks, as well as a significant need for complex construction tasks. Most SMEs have reported an increased need for mobile and flexible automation systems, perceiving humanoid robots as a potential solution within the next five years. This study presents industry sector specific automation needs and underlines the requirement of mobile, versatile, and safe systems with a low-code approach, to decrease entry barriers for SMEs and provide value to their specific needs.
Introduction
The challenges encountered in the design of multi-robot teams (MRT) highlight the need for different levels of human involvement, creating human-in-the-loop multi-robot teams. By integrating human cognitive abilities with the functionalities of the robots in the MRT, we can enhance overall system performance. Designing such a human-in-the-loop MRT requires several decisions based on the specific context of application. Before implementing these systems in real-world scenarios, it is essential to model and simulate the various components of the MRT to evaluate their impact on performance and the different roles a human operator might play.
Methods
We developed a simulation framework for a human-in-the-loop MRT using the Java Agent DEvelopment framework (JADE) and investigated the effects of different numbers of robots in the MRT, MRT architectures, and levels of human involvement (human collaboration and human intervention) on performance metrics.
Results
Results show that task execution outcomes and request completion times (RCT) improve with an increasing number of robots in the MRT. Human collaboration reduced the RCT, while human intervention increased the RCT, regardless of the number of robots in the MRT. The effect of system architecture was only significant when the number of robots in the MRT was low.
Discussion
This study demonstrates that both the number of robots in a multi-robot team (MRT) and the inclusion of a human in the loop significantly influence system performance. The findings also highlight the value of simulation as a cost- and time-efficiency strategy to evaluate MRT configurations prior to real-world implementation.
Motivated by the application of using model predictive control (MPC) for motion planning of autonomous mobile robots, a form of output tracking MPC for non-holonomic systems and with non-convex constraints is studied. Although the advantages of using MPC for motion planning have been demonstrated in several papers, in most of the available fundamental literature on output tracking MPC it is assumed, often implicitly, that the model is holonomic and generally the state or output constraints must be convex. Thus, in application-oriented publications, empirical results dominate and the topic of proving completeness, in particular under which assumptions the target is always reached, has received comparatively little attention. To address this gap, we present a novel formulation of the finite horizon optimal control problem. Using this in an MPC algorithm, convergence to a desired target can be guaranteed under realistic assumptions that can be verified in relevant real-world scenarios.
Der Vortrag beleuchtet, wie der ISOBUS-Standard (ISO 11783) als herstellerübergreifende Kommunikationsplattform zunehmend auch im Spezialkulturbereich – insbesondere im Plantagen- und Obstbau – Anwendung finden kann. Während ISOBUS im Ackerbau längst zur Grundlage für Präzisionslandwirtschaft geworden ist, stehen Plantagenbetriebe oft noch vor fragmentierten, proprietären Einzellösungen.
Anhand praxisnaher Beispiele aus Sprühtechnik, Ernte und digitaler Dokumentation wird aufgezeigt, wie ISOBUS die Integration und Automatisierung im Plantagen- und Sonderkulturbereich verbessern kann – durch Effizienzsteigerung, Ressourcenschonung und Zukunftssicherheit. Ziel ist es, den Nutzen standardisierter Kommunikation für kleine und mittelgroße landwirtschaftliche Betriebe greifbar zu machen und das Potenzial für intelligente, vernetzte Maschinen zu verdeutlichen.
For over a decade, autonomous solutions were mainly presented by small and medium-sized companies, innovative start-ups, and as research projects. At the same time, the so-called traditional big players in the agricultural industry acted reserved. However, projects for inspecting technology solutions and understanding legal opportunities and constraints were presented, e.g., by AGCO, John Deere, and CNHi. During the past two years, this strategy has drastically changed. Following, but not limited to, the success of the European industry collaborations Advanced Automation and Autonomy (A3) by Claas, AgXeed, and Amazone and Combined Powers by Lemken and Krone, there is a remarkable push towards autonomous field operations. Thus, autonomous solutions have become a significant topic in the agricultural industry. Most of the constraints for autonomous operations in agriculture can be traced back to three questions, which contain the most important answers for autonomy in agriculture:
• How must the role and requirements for functional safety in autonomous systems, characterized by the absence of a local operator, the driver, be described?
• What components and setup of sensor sets allow for autonomous operations, and how can sensor sets be evaluated for various purposes in the agricultural industry?
• How can autonomous operation, responsibility, and the underlying liability aspects be distributed over operational agricultural systems, especially in classic tractor-implement combinations?
Several agricultural industry associations have launched specific projects to answer the relevant aspects of these questions. For example, the European Agricultural Machinery Association (CEMA) is running the Safety in Autonomous Functions initiative (PT4), and the Agricultural Industry Electronics Foundation (AEF e.V.) started the project team Autonomy in Agriculture (AEF AUT). Other initiatives concentrate on obviously contributing aspects, such as the security of services, broad bandwidth wireless and long-distance communication, and the ethical impacts of autonomous operations. In an informative matter, this short paper will report and summarize two of these activities.
The agricultural sector is undergoing a profound transformation driven by technological innovation, demographic shifts, and growing sustainability demands. As labor shortages and economic pressures intensify, the implementation of high levels of automation in agricultural machinery is evolving from a visionary concept to an urgent necessity. Currently the automation in agricultural engineering builds upon well-established technologies such as satellite-based guidance systems, variable rate control (VRC), and section control. These solutions form the backbone of modern precision farming and provide a stable foundation for advancing toward higher levels of autonomy.
Autonomy in Agriculture is not limited to, but includes autonomous navigation, real-time object detection for enhanced safety, and collaborative multi-machine operations. While such capabilities are widely explored in on-road contexts, their adaptation to agricultural environments requires addressing unique challenges – including unstructured terrain, environmental variability, and multifaceted task requirements. Key concepts like Operational Design Domains (ODD), originally developed in the automotive sector, are target for being reinterpreted for off-road use. Standardization efforts, including the adoption of tools and protocols from the automotive domain, play a critical role in ensuring reliable development and testing of autonomous systems tailored to agricultural applications.
This context highlights the importance of sector-wide collaboration. Industry groups, academic institutions, and international associations such as VDMA, CEMA, and ISO committees are jointly working to define technical standards, safety protocols, and validation strategies. A particular challenge remains in the fragmentation of requirements due to bilateral negotiations between sensor providers and OEMs. Harmonizing processes, methods, and metrics promises to streamline development, reduce redundancy, and support scalable, reliable solutions across industries.
This contribution aims to provide an integrated overview of current developments, cross-sector initiatives, and future directions for automation in agriculture. It serves as an invitation to interdisciplinary exchange and collaboration.
The agricultural industry is undergoing a significant transformation with the increasing adoption of autonomous technologies. Addressing complex challenges related to safety and security, components and validation procedures, and liability distribution is essential to facilitate the adoption of autonomous technologies. This paper explores the collaborative groups and initiatives undertaken to address these challenges. These groups investigate inter alia three focal topics: 1) describe the functional architecture of the operational range, 2) define the work context, i.e., the realistic scenarios that emerge in various agricultural applications, and 3) the static and dynamic detection cases that need to be detected by sensor sets. Linked by the Agricultural Operational Design Domain (Agri-ODD), use case descriptions, risk analysis, and questions of liability can be handled. By providing an overview of these collaborative initiatives, this paper aims to highlight the joint development of autonomous agricultural systems that enhance the overall efficiency of farming operations.
Over the past decade, the popularity of cobots (collaborative robots) has grown, largely due to their operator-friendly usage. When selecting a cobot or robot for a specific application, it is essential to consider which model best aligns with the desired process. The objective of this work is to introduce a method for evaluating the three-dimensional position performance of a given process to identify the optimal technical solution.
There is a growing demand for autonomous mobile robots capable of navigating unstructured agricultural environments. Tasks such as weed control in meadows require efficient path planning through an unordered set of coordinates while minimizing travel distance and adhering to curvature constraints to prevent soil damage and protect vegetation. This paper presents an integrated navigation framework combining a global path planner based on the Dubins Traveling Salesman Problem (DTSP) with a Nonlinear Model Predictive Control (NMPC) strategy for local path planning and control. The DTSP generates a minimum-length, curvature-constrained path that efficiently visits all targets, while the NMPC leverages this path to compute control signals to accurately reach each waypoint. The system’s performance was validated through comparative simulation analysis on real-world field datasets, demonstrating that the coupled DTSP-based planner produced smoother and shorter paths, with a reduction of about 16% in the provided scenario, compared to decoupled methods. Based thereon, the NMPC controller effectively steered the robot to the desired waypoints, while locally optimizing the trajectory and ensuring adherence to constraints. These findings demonstrate the potential of the proposed framework for efficient autonomous navigation in agricultural environments.
This study explores the use of socially assistive robots (SARs) for behavioural coaching for healthy habit formation. We conducted four focus group discussions with nineteen end users to understand their needs and expectations for SAR coaches. We performed a thematic and narrative analysis of the data collected. Our findings emphasise the significance of SARs in assisting individuals and equipping them with the skills for independent health management after the intervention ends. The design requirements generated are centred around interaction, ethics, and environment and are justified by linking them with established behavioural theories. These requirements will help guide the development of robotic interventions that support long-term habit formation.