TUM - Institute for Cognitive Systems’ Post

We are happy to welcome Prof. Daniel J. Preston from Rice University at TUM - Institute for Cognitive Systems on 27 September. Prof. Preston will offer us an exciting guest talk. Title: Material-Enabled Technologies for Soft and Fluidic Robots. Abstract: The emerging field of soft robotics, which incorporates unconventional or compliant materials in autonomous systems, has simultaneously reshaped traditional robotics applications and introduced new use cases for robots. However, many useful classes of materials remain relatively unexplored, and furthermore, the vast majority of soft robotics research has targeted actuation and sensing, with power and control schemes still relying on bulky, rigid electronic components. My research program addresses open questions in these domains by applying our expertise in energy, fluids, and materials. For instance, biotic materials—non-living materials derived from living organisms—have remained underutilized in robotics, despite having played a role in human development since the times our early ancestors wore animal hides as clothing and used bones for tools. In the first part of my talk, I describe how we repurposed an inanimate spider as a ready-to-use actuator requiring only a single fabrication step, initiating the area of “necrobotics” in which biotic materials are used as robotic components. The second part of my talk focuses on assistive wearable robots, which currently rely on bulky and hard control systems and power supplies, or alternatively require cumbersome tethers to external infrastructure. To address this limitation, my group has developed completely soft fluidic digital logic components fabricated entirely from textiles. Our fluidic logic platform enables integrated memory, decision making, and the ability to interact with and adapt to stimuli and the environment, all without the use of rigid valves or electronics. Meanwhile, we address limitations in power delivery by developing “self-powered” textile-based wearable robots that harvest energy from the motion of the human body. The integration of fluidic logic and energy harvesting in textile architectures represents an important step toward fully soft, self-sufficient wearable robots that are as comfortable, resilient, and practical as everyday clothing. Location: 2026, Karlstraße-Seminarraum (2906.02.026) Time: 10:00 a.m. Address: Karlstr. 45(2906)/II, 80333 München Highlights from publications: Embedded Fluidic Sensing and Control with Soft Open-Cell Foams https://lnkd.in/d2XZiWCp Fluidically programmed wearable haptic textiles https://lnkd.in/gdyABuNC  Logic-enabled textiles https://lnkd.in/dRQMxN2u  A wearable textile-based pneumatic energy harvesting system for assistive robotics https://lnkd.in/g29mHNDm #soft_robotics #smart_textile #fluidic_logic #energy_harvesting #textile_and_robotics

Congratulations, Prof. Gordon Cheng, for becoming an RSJ Fellow this year! 🎉 Prof. Cheng was among the four fellows honored at the 42nd Annual Conference of The Robotic Society of Japan (RSJ). He was honored for his long-standing contributions to “science and technology”! 👏 Heartfelt congrats from the ICS team! 🙏

The next Doctoral Research Seminar next Monday will present 'Enjoying Time with Robots: Design Interactive Robots That Are Fun to Interact With' by prof. Albrecht Schmidt and Sven Mayer.🤖 July 1st, 2024, 10:30 am - 11:30 am in room 2026, Karlstr. 45. What does it take to make interacting with someone or something enjoyable? What qualities make us want to work with a particular person? When do we enjoy interacting with people, animals or things? Can we apply the answers to these questions to human-robot interaction? How can we design systems with higher levels of autonomy, such as smart environments, robots, and cars, so that we want to use them and interact with them? In particular, effective teaching of these systems is crucial to making them useful, enforcing desired behavior, and correcting undesired actions. In-situ learning and adaptation to specific contexts (e.g. culture, user type, preferences) are essential for effective real-world learning. However, motivating humans to teach machines is the key challenge. We argue that curiosity-driven behavior can lead to more natural interactions and increase human willingness to teach. We see this as a first step towards designing interactive robots that are fun to interact with. We hope to discuss with you our experiences from research and teaching in this area. #human-robot #interaction #robotics

📢The upcoming Doctoral Research Seminar this Monday will present "Learning while Sleeping: Integrating Sleep-Inspired Consolidation with Human Feedback Learning" by Imene Tarakli 🛌 🧠 🗓️June 24th 10:30-11:30 in room 2026, Karlstr. 45 Sleep plays a vital role in developmental learning. It allows the brain to consolidate daily learning experiences by replaying the memories accumulated throughout the day. In this work, we take inspiration from sleep and propose the Inverse Forward Offline Reinforcement Model (INFORM), a scalable framework that first learns a set of behaviours from human evaluative feedback, then consolidates the learning by applying an offline inverse reinforcement learning to the memorised trajectories. Experimental results demonstrate that INFORM is a feedback-efficient method that effectively learns an optimal policy that align with the intended behaviour of the human. A comparative analysis shows that the learnt policies are robust to dynamics changes in the environment and the recovered rewards allows the robot to be autonomous in its learning. #humanoid #robotics

🎉 Congratulations to our colleagues Fengyi Wang, Xiangyu Fu, prof. Nitish Thakor and prof. Gordon Cheng. Their paper "Object Classification Utilizing Neuromorphic Proprioceptive Signals in Active Exploration: Validated on a Soft Anthropomorphic Hand” has been accepted for publication for IEEE RAS EMBS 10th International Conference on Biomedical Robotics and Biomechatronics (BioRob 2024) taking place in Heidelberg (Germany) from 1-4 September 2024. 📅

College student Fengyi Wang just presented groundbreaking research on "Enhancing Roughness Classification Accuracy Using Neuromorphic Sensory Encoding and Spiking Neural Networks" at the Technical University of Munich Institute of Advanced Study event! This impressive work results from a successful collaboration between TUM - Institute for Cognitive Systems and John Hopkins University. Congratulations to Fengyi Wang and the team for their outstanding contribution to the field! #research #neuromorphic #spikingneuralnetworks #collaboration Nitish Thakor Mark Iskarous Gordon Cheng

The next Doctoral Research Seminar will present "SNAPP, An Agile Robotic Fish with 3-D Maneuverability for Open Water Swim " by Timothy Ng, HKU. 🤖 April 29th, 2024, 10:30 am - 11:30 am in room 2026, Karlstr. 45. Fish exhibit impressive locomotive performance and agility in complex underwater environments, using their undulating tails and pectoral fins for propulsion and maneuverability. Replicating these abilities in robotic fish is challenging; existing designs focus on either fast swimming or directional control at limited speeds, mainly within a confined environment. To address these limitations, we designed Snapp, an integrated robotic fish capable of swimming in open water with high speeds and full 3-dimensional maneuverability. A novel cyclic-differential method is layered on the mechanism. It integrates propulsion and yaw steering for fast course corrections. Two independent pectoral fins provide pitch and roll control. We evaluated Snapp in open water environments and demonstrated significant improvements in speed and maneuverability, achieving swimming speeds of 1.5 m/s (1.7 body lengths per second) and performing complex maneuvers, such as a figure-8 and S-shape trajectory. Instantaneous yaw changes of 15◦ in 0.4 s, a minimum turn radius of 0.85 m, and maximum pitch and roll rates of 3.5 and 1 rad/s, respectively, were recorded. Our results suggest that Snapp’s swimming capabilities have excellent practical prospects for open seas and contribute significantly to developing agile robotic fishes. #locomotive #roboticfish #innovation

The upcoming Doctoral Research Seminar next Monday will present "Bioinspired Fundamentals and Mechanisms for the Design of a Running Humanoid Robot“ by Konrad Fründ (German Aerospace Center (DLR))🤖 April 22nd, 2024, 10:30 – 11:30 in room 2026, Karlstr. 45 📅 The field of humanoid robots is currently experiencing significant growth, with most humanoids focusing on industrial tasks within walkable distances. However, the ability to rapidly traverse complex terrain might become one of the future tasks for humanoid robots, to solve their given tasks efficiently. Within the seminar we investigate the bioinspired fundamentals and mechanisms that drive the design of a running humanoid robot. We will explore the bioinspired principles from the remarkable locomotion capabilities observed in humans which can be translated into the design and control of humanoid robots. The fundamental biomechanical functions of the human running gait will be discussed and how they can serve as guidelines for innovative humanoid robot designs. A focus is then given to the kinematics of humanoid robots and their joint axes to investigate the effect of oblique axes on bipedal locomotion. The seminar talk will provide valuable insights into the interdisciplinary research field of biomechanics, human anatomy, robotics, and how it can push the boundaries of what humanoid robots can achieve. #humanoid #robotic #locomotion

Congratulations to Youssef Michel, Matteo Saveriano, and Dongheui Lee! The paper on "A Novel Safety-Aware Energy Tank Formulation Based on Control Barrier Functions " has been accepted for publication in the IEEE Robotics and Automation Letters (RA-L) 🎉 🔬 💪 In this work, they propose a novel formulation for energy tanks based on Control Barrier Functions (CBF). Their approach can simultaneously handle energy constraints to ensure passivity and enforce power limits in the system to enhance safety. Furthermore, their approach overcomes the discrete switching nature of classical energy tanks, ensuring smooth control commands. To achieve their desiderata, they formulate the tank as a second-order dynamical system, where they exploit CBF and Higher-Order CBF to obtain theoretical guarantees on fulfilling the energy and power constraints in the system. Furthermore, they derive conditions related to the tank design to ensure the passivity of the controlled robot. Their proposed approach is tested in a series of robot experiments where they validate their approach on tasks such as variable stiffness and force control, and in a scenario where it is desired to constrain the kinetic energy in the system. #Robotics #Technology #Innovation