Fraunhofer Institute for Material Flow and Logistics IMLThere is a growing demand for dynamic robotics, i.e., highly dynamic systems that can perform a variety of movements and actions. These robots are generally designed to perform complex and fast movements in a variety of environments. In logistics, highly dynamic robots can be a significant lever for process optimization in terms of speed and efficiency.
Dynamic Robotics: Making processes time-efficient
Dynamic Robotics: speed and acceleration
Robotic solutions are playing an increasingly important role in the logistics industry, as they can perform a wide range of tasks, reduce the workload on employees, and contribute to the automation of the industry. Dynamic robotics, or (highly) dynamic systems, are both static and mobile systems that differ from previously used robotic systems in terms of their increased speed or acceleration.
The robots currently used in logistics are primarily designed for specific tasks and support processes within a limited time frame. Additionally, it is often necessary to specially plan or redesign warehouses or production environments to enable robots to operate more efficiently than conventional systems, such as conveyor belts, which have limited mobility.
The development of high-dynamic robotics primarily focuses on optimizing processes for greater time efficiency, particularly in logistics operations that can be executed more rapidly. However, due to the increased speed and acceleration of dynamic systems, it is essential to consider physical effects during the planning stage. Factors such as braking distance, adhesion limits, and slip effects directly impact the practical use of highly dynamic robots.
Comprehensive Support in Dynamic Robotics
Our services include both professional and technological know-how for the implementation of customized high-dynamic robotics solutions:
- comprehensive development and integration of dynamic mechatronic system
- developing solutions for dynamic control tasks
- simulation-based AI
- simulation studies of physics and material flows
- potential analysis for the use of highly dynamic systems in logistics processes
The research field of dynamic robotics requires a certain level of digitalization and automation maturity. Together, we examine the current state of automation and determine the extent to which dynamic robotics can be used. The construction of robots capable of performing dynamic and versatile movements is a complex task that involves many obstacles, such as the engine, sensors, and control mechanisms.
Areas of application for dynamic robotics in logistics
Intralogistics is facing profound changes as demographic shifts reduce the number of available workers while the volume of goods to be handled grows. Companies must increasingly replace manual processes with automation in order to secure material flows and achieve efficiency gains despite a shortage of specialists. This is creating a growing market for flexible automation solutions for intralogistics processes, in which multi-purpose and AI-based robots such as highly dynamic mobile robots play a central role. The use of automation and robotics solutions frees employees from routine tasks and gives them more time for value creation activities.
Whether in warehousing, picking, or transport: in the infrastructure-reduced logistics of the future, flexible autonomous systems are increasingly replacing rigid automation solutions. Closed systems in particular offer a suitable environment for making processes more time-efficient with the help of dynamic robotics. The speed of highly dynamic systems means that safety aspects that were not considered until now are now becoming more important. Both the human factor and the combination of various systems that must interact via suitable interfaces lead to unpredictable situations during operation and must be taken into account when planning and using dynamic systems.
“The demand for dynamic robotics is growing, as highly dynamic systems can make processes more time efficient. However, during development, the physical dynamics of the system must also be considered for the regulation technology.”
Nils Gramse, Research Scientist in the field of Dynamic Robotics at Fraunhofer IML
Research halls and laboratories for dynamic robotics
In logistics, there is a growing need for flexible, autonomous robot systems that can move safely and efficiently in dynamic environments – especially against the backdrop of a shortage of specialists and increasing demands for process automation. The research infrastructure at Fraunhofer IML is designed for the research and development of dynamic systems.
Developing prototypes
At the Fraunhofer IML Prototype Center, we develop and manufacture customized robotics platforms that can be used for a wide range of logistics applications thanks to their modular sensors, intelligent control systems, and robust mechanics. The prototype center's areas of expertise include both the linking of different disciplines (including mechanical engineering, electrical engineering, computer science, and robotics) and the use and combination of various manufacturing technologies.
Testing systems
Localization, motion capturing, and communication for autonomous systems: The PACE Lab is a testing ground where autonomous systems are developed and tested. It offers a globally unique research environment for high-precision localization, wireless communication, and the development of autonomous systems in industrial settings.
Our research focus in dynamic robotics
Fraunhofer IML is the leading research institute in the field of self-driving transport vehicles and autonomous mobile robots for logistics. In the field of dynamic robotics, researchers are primarily concerned with the following topics:
- safe control strategies for unusual driving situations
- localization with highly nonlinear dynamics
- advanced condition estimation in case of sensor malfunctions or dynamic environmental conditions
- reinforcement learning of regulations for highly dynamic robotic systems
- Generative AI (GenAI) for process control
Dynamic robotics and humanoid robotics
Dynamic robotics and humanoid robotics are closely related, as both fields aim to develop robots that are capable of performing complex and dynamic tasks. The development of human-like dynamic systems is currently on the rise. The two fields support each other by exchanging technologies and methods to design robots that are more human-like and effective in dynamic environments:
- Motion dynamics
Dynamic robotics and humanoid robotics are closely related, as both fields aim to develop robots that are capable of performing complex and dynamic tasks. The development of human-like dynamic systems is currently on the rise. The two fields support each other by exchanging technologies and methods to design robots that are more human-like and effective in dynamic environments: - Adapability
Both humanoid robots and dynamic robotics systems must be able to adapt to changing environments and situations. This requires advanced sensors, control systems, and artificial intelligence to respond to unforeseen events. - Interaction and Autonomy
Humanoid robots are increasingly designed to interact with humans. High Dynamic robotics helps ensure that these interactions run smoothly and naturally by developing technologies that enable fast and precise responses to human actions. - Technological Challenges
Both areas face similar technological challenges, such as the integration of artificial intelligence, the development of efficient drive systems, and the improvement of energy efficiency. Solutions found in one area can often be transferred to the other.
Training Highly Dynamic Robotics
When developing and training autonomous, scalable, and real-time capable systems, methods and logic from machine learning and artificial intelligence are increasingly being used. As a highly complex system, a robot must not only learn how the interaction between mechanics, sensors, and control engineering works, but also how to respond to external influences. For this reason, Fraunhofer IML is researching how reinforcement of regulations for highly dynamic robot systems works. Reinforcement learning (RL) is an area of machine learning in which an agent learns how to behave in an environment to maximize a certain reward.
In terms of robotics, this means that robots learn to perform tasks through trial and error by learning from their interactions with the environment. A robot trained with reinforcement learning receives feedback in the form of rewards or penalties. This feedback depends on how well the robot's actions contribute to achieving a goal. The robot then tries to adjust its strategy to maximize the cumulative reward over time. The goal is for the robot to learn on its own and adapt to new situations without having to be explicitly programmed for each specific task.
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Dynamic robotics: Our references
evoBOT®
Full flexibility, less complexity: The evoBOT® combines the advantages of humanoid robots with a simple, modular design. It is based on the principle of an inverted pendulum, can move in confined spaces, and can pick up and put down loads at any height.
O³dyn
From concept to prototype implementation, O³dyn combines performance with dynamics and flexibility. With a travel speed of up to 36 km/h, it transports pallets omnidirectionally from inside to outside and back again.
LoadRunner
The LoadRunner has enabled the Fraunhofer IML to establish a new generation of self-driving transport vehicles. With its dynamic performance and flexible direction of travel, this autonomous high-speed vehicle is perfectly suited to sorting and distribution processes.
Understanding dynamic robotics: 7 questions and answers
What is dynamic robotics?
Dynamic robotics generally refers to robotics dealing with the dynamic interaction and movement of robots in complex and unpredictable environments. The dynamics of the movements must be taken into account during planning, in particular the impact of physical effects on the robot, such as adhesion limits, slip effects, or braking distances.
What technologies are used in dynamic robotics?
Dynamic robotics leverages technologies such as machine learning (ML), artificial intelligence (AI), and communication systems. These technologies enable robots to learn independently and adapt to various environments. Machine learning optimizes the dynamic movement of mobile robots and helps bridge the sim-to-real gap, allowing robots to operate precisely and safely in logistics and other fields.
How do dynamic robotics differ from traditional robotics?
Dynamic robotics focuses on the development of robots that can move flexibly and dynamically in changing environments, whereas traditional robotics is often limited to static or preprogrammed movements. This dynamism requires advanced algorithms and sensors to enable complex movements such as running or jumping while coordinating the robot's own speed.
Which industries benefit most from dynamic robotics?
Industries such as logistics, manufacturing, and healthcare benefit most from high dynamic robotics, as these robotics systems can significantly accelerate processes and make them more efficient.
In logistics in particular, robots can be used to map transport and storage processes much more quickly. Processes that could be mapped much more quickly in theory offer the greatest potential for optimization through dynamic robotics.
What are the challenges involved in implementing dynamic robotics?
When implementing dynamic robotics, challenges such as human-technology interaction, safety, and the precise localization of robots are a priority. Furthermore, it is easier to use individual, isolated systems than to coordinate the interaction of many systems that have to communicate and interact with each other. In addition, cooperation between various fields of expertise in robotics, computer science, and mechanical engineering is needed to bridge the gap between theory and practice and develop practical, application-oriented solutions.
What safety aspects must be considered when using dynamic robotics?
When using dynamic robotics, safety risks such as the increased speed of the robots and the unpredictability of human behavior must be taken into account. Before commissioning, a comprehensive risk assessment must be carried out in which potential hazards posed by the dynamic movements, speeds, and forces of the robots are systematically identified and minimized by appropriate safety measures. These include physical protective fences, safety zones, emergency stop switches, collision-avoidance sensors and control strategies, as well as redundant safety architectures to reliably protect people and facilities. In addition, the combination of different systems and their interfaces is a challenge, as unpredictable situations can arise.
What are the future trends in the field of dynamic robotics?
Future trends in dynamic robotics include the development of humanoid robotics, the design of robot systems that are not limited by the constraints of human capabilities, and systems that ensure increased flexibility.
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