Institute Homepage
Institute Homepage EN Sign In

Publications

DEPARTMENTS

Emperical Interference

Haptic Intelligence

Modern Magnetic Systems

Perceiving Systems

Physical Intelligence

Robotic Materials

Social Foundations of Computation

Research Groups

Autonomous Vision

Autonomous Learning

Bioinspired Autonomous Miniature Robots

Dynamic Locomotion

Embodied Vision

Human Aspects of Machine Learning

Intelligent Control Systems

Learning and Dynamical Systems

Locomotion in Biorobotic and Somatic Systems

Micro, Nano, and Molecular Systems

Movement Generation and Control

Neural Capture and Synthesis

Physics for Inference and Optimization

Organizational Leadership and Diversity

Probabilistic Learning Group

Topics

Robot Learning

Conference Paper

2022

Autonomous Learning

Robotics

AI

Career

Award

Physical Intelligence Article In vivo diabetic wound healing with nanofibrous scaffolds modified with gentamicin and recombinant human epidermal growth factor Dwivedi, C., Pandey, I., Pandey, H., Patil, S., Mishra, S. B., Pandey, A. C., Zamboni, P., Ramteke, P. W., Singh, A. V. Journal of Biomedical Materials Research Part A, 106(3):641-651, March 0
Abstract Diabetic wounds are susceptible to microbial infection. The treatment of these wounds requires a higher payload of growth factors. With this in mind, the strategy for this study was to utilize a novel payload comprising of Eudragit RL/RS 100 nanofibers carrying the bacterial inhibitor gentamicin sulfate (GS) in concert with recombinant human epidermal growth factor (rhEGF); an accelerator of wound healing. GS containing Eudragit was electrospun to yield nanofiber scaffolds, which were further modified by covalent immobilization of rhEGF to their surface. This novel fabricated nanoscaffold was characterized using scanning electron microscopy, Fourier transform infrared spectroscopy, and X‐ray diffraction. The thermal behavior of the nanoscaffold was determined using thermogravimetric analysis and differential scanning calorimetry. In the in vitro antibacterial assays, the nanoscaffolds exhibited comparable antibacterial activity to pure gentemicin powder. In vivo work using female C57/BL6 mice, the nanoscaffolds induced faster wound healing activity in dorsal wounds compared to the control. The paradigm in this study presents a robust in vivo model to enhance the applicability of drug delivery systems in wound healing applications. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 106A: 641–651, 2018.
DOI URL BibTeX
Physical Intelligence Article A Palm-Sized Four-Legged Climbing Robot Using Flat Dry Elastomer Adhesives Unver, O., Sitti, M. 0 BibTeX
Physical Intelligence Article A Tri-Legged Capsule Endoscope Robot Using Micro-Patterned Adhesives Glass, P., Cheung, E., Sitti, M. 0 BibTeX
Movement Generation and Control Conference Paper A Whole-Body Model Predictive Control Scheme Including External Contact Forces and CoM Height Variations 0 BibTeX
Physical Intelligence Article ADHESIVE BEHAVIOR OF VERTICAL AND ANGLED POLYMER MICROFIBER ARRAYS Murphy, M. P., Aksak, B., Sitti, M. 0 BibTeX
Autonomous Motion Article Cerebral or spinal level interaction of rhythmic and discrete movements during two-joint arm task Mohajerian, P., Mistry, M., Schaal, S. Journal of Neurophysiology, 0, clmc BibTeX
Thesis Change-point Detection and Kernels Methods 0 BibTeX
Physical Intelligence Article Chemotactic Behavior of Bacteria Propelled Microbeads in Linear Microfluidic Gradients Kim, D., Liu, A., Sitti, M. 0 BibTeX
Article Classified Regression for Bayesian Optimization: Robot Learning with Unknown Penalties Marco, A., Baumann, D., Hennig, P., Trimpe, S. 0, Submitted to Journal (In preparation)
Learning robot controllers by minimizing a black-box objective cost using Bayesian optimization (BO) can be time-consuming and challenging. It is very often the case that some roll-outs result in failure behaviors, causing premature experiment detention. In such cases, the designer is forced to decide on heuristic cost penalties because the acquired data is often scarce, or not comparable with that of the stable policies. To overcome this, we propose a Bayesian model that captures exactly what we know about the cost of unstable controllers prior to data collection: Nothing, except that it should be a somewhat large number. The resulting Bayesian model, approximated with a Gaussian process, predicts high cost values in regions where failures are likely to occur. In this way, the model guides the BO exploration toward regions of stability. We demonstrate the benefits of the proposed model in several illustrative and statistical synthetic benchmarks, and also in experiments on a real robotic platform. In addition, we propose and experimentally validate a new BO method to account for unknown constraints. Such method is an extension of Max-Value Entropy Search, a recent information-theoretic method, to solve unconstrained global optimization problems.
arXiv URL BibTeX
Physical Intelligence Article Compliance effects in the shear failure and friction of bio-inspired microfiber arrays. Piccardo, M., Chateauminois, A., Frétigny, C., Pugno, N. M., Sitti, M. 0 BibTeX
Miscellaneous Cutaneous Electrohydraulic (CUTE) Wearable Devices for Expressive and Salient Haptic Feedback 0 BibTeX
Neural Capture and Synthesis Conference Paper DINER: Depth-aware Image-based Neural Radiance Fields In 0 BibTeX
Neural Capture and Synthesis Conference Paper DINER: Depth-aware Image-based Neural Radiance Fields In 0 BibTeX
Physical Intelligence Article DRAFT: DESIGN AND NUMERICAL MODELING OF AN ON-BOARD CHEMICAL RELEASE MODULE FOR MOTION CONTROL OF BACTERIA-PROPELLED SWIMMING MICRO-ROBOTS Behkam, B., Nain, A. S., Amon, C. H., Sitti, M. 0 BibTeX
Physical Intelligence Article Enhancing Adhesion and Friction of Biologically Inspired Polymer Microfibers with a Viscous Oil Coating Cheung, E., Sitti, M. 0 BibTeX
Physical Intelligence Article Feedback of surfaces at the Micro/Nano scale Sitti, M., Horiguchi, S., Hashimoto, H. 0 BibTeX
Physical Intelligence Article Geckobot: A Palm Size Gecko-Like Climbing Robot Using Flat Dry Elastomer Adhesives Unver, O., Sitti, M. 0 BibTeX
Conference Paper Goal-conditioned Offline Planning from Curious Exploration Bagatella, M., Martius, G. In Advances in Neural Information Processing Systems 36, 0 BibTeX
Conference Paper Goal-conditioned Offline Planning from Curious Exploration Bagatella, M., Martius, G. In Advances in Neural Information Processing Systems 36, 0
Curiosity has established itself as a powerful exploration strategy in deep reinforcement learning. Notably, leveraging expected future novelty as intrinsic motivation has been shown to efficiently generate exploratory trajectories, as well as a robust dynamics model. We consider the challenge of extracting goal-conditioned behavior from the products of such unsupervised exploration techniques, without any additional environment interaction. We find that conventional goal-conditioned reinforcement learning approaches for extracting a value function and policy fall short in this difficult offline setting. By analyzing the geometry of optimal goal-conditioned value functions, we relate this issue to a specific class of estimation artifacts in learned values. In order to mitigate their occurrence, we propose to combine model-based planning over learned value landscapes with a graph-based value aggregation scheme. We show how this combination can correct both local and global artifacts, obtaining significant improvements in zero-shot goal-reaching performance across diverse simulated environments.
URL BibTeX
Physical Intelligence Article Highly Dynamic Bio-Inspired Legged Running on Water Surface Sitti, M. 0 BibTeX
Physical Intelligence Article IEEE TRANSACTIONS ON ROBOTICS SICILIANO, B., HOLLERBACH, J., WALKER, I., ZELINSKY, A., CASALS, A., DE LUCA, A., LUH, P. B., VOLZ, R. A., TAYLOR, R. H., BEKEY, G. A., others, 0 BibTeX
Article InterCap: Joint Markerless 3D Tracking of Humans and Objects in Interaction 0 BibTeX
Physical Intelligence Article Magnetic Putty as A Reconfigurable, Recyclable, And Accessible Soft Robotic Material Li, M., Pal, A., Byun, J., Gardi, G., Sitti, M. Advanced Materials, 35(48):2304825, 0 DOI BibTeX
Physical Intelligence Article Modeling Six Degrees of Freedom Rigid-Body Motion of a Thermocapillary Microswimmer Tabak, A., Amador, G., Sitti, M. 0 BibTeX
Physical Intelligence Article Non-Resonant Powering of Injectable Nanoelectrodes Enables Wireless Deep Brain Stimulation in Freely Moving Mice 0 BibTeX
Conference Paper Optimal gamification can help people procrastinate less 0 BibTeX
Physical Intelligence Article Particle Rolling on a Fibrillar Interface Abusomwan, U., Sitti, M. 0 BibTeX
Conference Paper Reinforcement Learning of Phase Oscillators for Fast Adaptation to Moving Targets 0 BibTeX
Physical Intelligence Article Robotics Research Woodward, M. A., Sitti, M., Martin, A. E., Post, D. C., Schmiedeler, J. P., Williams, S., Indelman, V., Kaess, M., Roberts, R., Leonard, J. J., others, 0 BibTeX
Physical Intelligence Article Robotics Research Tong, C. H., Furgale, P., Barfoot, T. D., Guizilini, V., Ramos, F., Chen, Y., T\uumová, J., Ulusoy, A., Belta, C., Tenorth, M., others, 0 BibTeX
Physical Intelligence Article Roll and height control for legged locomotion on the water surface Thatte, N., Khoramshahi, M., Ijspeert, A., Sitti, M. 0 BibTeX
Article Tail assisted Pitch Control in Lizards, Robots, and Dinosaurs. 0 BibTeX
Book Testtitel Testauthor, 0 BibTeX
Rationality Enhancement Conference Paper Toward a normative theory of (self-)management by goal-setting Singhi, N., Mohnert, F., Prystawski, B., Lieder, F. 0 BibTeX
Conference Paper Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations Zadaianchuk, A., Kleindessner, M., Zhu, Y., Locatello, F., Brox, T. In 0
In this paper, we show that recent advances in self-supervised feature learning enable unsupervised object discovery and semantic segmentation with a performance that matches the state of the field on supervised semantic segmentation 10 years ago. We propose a methodology based on unsupervised saliency masks and self-supervised feature clustering to kickstart object discovery followed by training a semantic segmentation network on pseudo-labels to bootstrap the system on images with multiple objects. We present results on PASCAL VOC that go far beyond the current state of the art (50.0 mIoU), and we report for the first time results on MS COCO for the whole set of 81 classes: our method discovers 34 categories with more than 20% IoU, while obtaining an average IoU of 19.6 for all 81 categories.
ArXiv BibTeX
Article Wireless soft millirobots for climbing three-dimensional surfaces in confined spaces 0 BibTeX
Physical Intelligence Article l< Feedback Surfaces at the MicroNaridScale:[Modeling and Experiments’. Sitti, M., Horiguchi, S., Hashimoto, H. 0 BibTeX
Book testnasim 0 BibTeX
Modern Magnetic Systems Article textes 0 BibTeX
Conference Paper 4D-DRESS: A 4D Dataset of Real-World Human Clothing With Semantic Annotations In 0 BibTeX
Physical Intelligence Article ナノ世界における 3 次元触覚フィードバック·インタフェース Horiguchi, S., Sitti, M., Hashimoto, H. 0 BibTeX