ICRA 2026 Workshop Proposal
The 2nd Workshop on Biomimetic Perception in Robotics: From Advanced Sensor Systems to Embodied Autonomy
Building on our IROS 2025 workshop “Biomimetic Perception in Robotics: From Biological Insights to Advanced Sensor Systems”, which focused on emerging bio-inspired sensing technologies such as lateral line perception (emulating fish mechanoreceptors for hydrodynamic sensing, Fig. 1A) and whisker-based tactile systems (inspired by mammalian vibrissae for object recognition in low-visibility environments, Fig. 1B), we propose the second edition for ICRA 2026. This workshop will focus on translating these paradigms into tangible robotics advancements, moving beyond individual sensor design to integrated systems that enable true autonomous decision-making.
We will explore the entire research pipeline: from fundamental biological insights and novel sensor technologies (inspired by touch, sonar, electroreception, and more) to the perception algorithms and cognitive architectures needed for processing this information. A key theme is multi-modal sensor fusion, mirroring the integrative capabilities of biological organisms. Applications include challenging domains like underwater exploration, navigation in cluttered or dark environments, and soft robotics, plus biomedical applications such as assistive and rehabilitation devices.
The workshop will unite leaders from robotics, biology, biomedical engineering, and materials science. Our goal is to identify key challenges, share breakthroughs, and chart a collaborative path toward creating robots with an adaptive autonomy informed by the principles of life itself.
The promotional video of our workshop for IROS 2025: https://www.youtube.com/watch?v=J-5Nzmza3zQ
The website of our workshop for IROS 2025: https://www.zheng-xingwen.com/workshops/iros2025/

Figure 1. Emerging bio-inspired sensing technologies
Invited speakers

EPFL, Switzerland

The Pennsylvania State University, USA

The University of Tokyo, Japan

University of Colorado Boulder, USA

Istituto Italiano di Tecnologia, Italy

Max Planck Institute of Animal Behavior, Germany

Tallinn University of Technology, Estonia

Singapore University of Technology and Design, Singapore

The University of Edinburgh, United Kingdom
Name | Affiliation | Country | Talk | |
---|---|---|---|---|
1 | Prof. Auke Ijspeert | EPFL | Switzerland | TBD |
2 | Prof. Bo Cheng | The Pennsylvania State University | USA | Underwater Robot Pressure Sensing and Perception for Station Keeping in Challenging Flow Conditions |
3 | Prof. Fumihito Arai | The University of Tokyo | Japan | TBD |
4 | Prof. Kaushik Jayaram | University of Colorado Boulder | USA | TBD |
5 | Prof. Lucia Beccai | Istituto Italiano di Tecnologia | Italy | TBD |
6 | Prof. Liang Li | Max Planck Institute of Animal Behavior | Germany | HydroTwin: A Pipeline for Exploring 3D Hydrodynamic Sensing Mechanisms in Free-Swimming Schooling Fish |
7 | Prof. Maarja Kruusmaa | Tallinn University of Technology | Estonia | Developing and scaling up distributed flow sensing for robots and underwater environments |
8 | Prof. Pablo Valdivia y Alvarado | Singapore University of Technology and Design | Singapore | Embedded Intelligence in Soft Robotics Enabled by Advanced Digital Fabrication Processes |
9 | Prof. Yunjie Yang | The University of Edinburgh | United Kingdom | Flexible Tomography for Life-like Perception and Autonomous Intelligence in Soft Robotics |
Tentative Schedule
Time | Activity | Details |
---|---|---|
8:00 – 8:05 | Welcome & Opening Remarks | Overview of workshop |
8:05 – 9:45 | Keynote Talks (4 speakers) | - 20 min talk + 5 min Q&A per speaker |
9:45 – 10:05 | Coffee Break | - 20 min interactive poster viewing |
10:05– 12:30 | Keynote Talks (5 speakers) | - 20 min talk + 5 min Q&A per speaker |
12:30 – 13:00 | Late-breaking Research Presentations | - 3 contributed submissions in total - 8 min presentation + 2 min Q&A each |
Organizers



Sponsors
Contact
If you have any questions about this workshop, please contact:
Xingwen Zheng <xingwen.zheng@zju.edu.cn>
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