Sustainability in SRL
Our Commitment To Sustainability
At the Soft Robotics Lab, we shape the laboratory activities and our research objectives for a sustainable future. For us, “future” means cutting-edge innovation and excellence in our research, but also a careful consideration of the environmental impact of our activities and a broad reflection on how technologies will affect our planet's evolution in the next years.
We believe that sustainable workplaces and practices are as crucial as framing our research aims for environmental care. Thus, we constantly look for sustainable fabrication and computational approaches to realize next-gen soft robots and we implement best lab practices to protect our environment. SRL adheres to the ETH Green Labs initiative and monitors its environmental impact through the LEAF tool (Laboratory Efficiency Assessment Framework).
Our team members are proud to share their commitment to having a positive environmental impact on both the society and scientific communities they work within.
“With my research on bio-intelligence and bio-hybrid machines, I would like to develop more sustainable biofabrication approaches and generate dynamical 3D cell culture models that could reduce the need for animal experimentation.”
Dr. Miriam Filippi - SRL Sustainability Officer
“I would like to develop a solution for robotics vision that runs real-time and realize that with a low-computing cost approach.”
Hehui Zheng - Green Roboticist 2023 Awardee & SRL Ambassador of the tree life
“My work is to optimize robotic design, and one of the optimization criteria can be to make it use fewer resources (fewer motors, less material) while retaining task performance. So when these robots may be manufactured at scale, they could use fewer resources than human-designed ones.”
Yasunori Toshimitsu
“My work aims to replace conventional DC-powered robotics with a greener robotic technology featuring high hardware efficiency and minimized acoustic pollution and thermal energy waste.”
Amirhossein Kazemipour
“I would like to use our hand-shaped robot to make recycling easier and cheaper, for example, sorting glass bottles.”
Barnabas Gavin Cangan
“With my work on fastening motion simulations, I will reduce computer usage and heat generation.”
Mike Yan Michelis
“I developed a high-performance computing framework for optimization, uncertainty quantification, and (inverse) reinforcement learning that efficiently uses the available computing hardware.”
Daniel Wälchli