Robots can clean up rivers, sort waste, or inspect renewable energy installations, but their own environmental footprint remains an open question. To address this, the robotics community now has a tool: the Robotics Eco-Label project, led by Bram Vanderborght at Vrije Universiteit Brussel in Belgium. It is among the projects funded by IEEE RAS sustainability grants, presented at ICRA in June.
A Sustainability Score for Robots
A robot’s footprint covers its entire life cycle, from rare earth extraction to manufacturing, through use and end-of-life. Until now, the community lacked dedicated tools to calculate it. The Robotics Eco-Label Toolkit, a lightweight online toolbox, breaks the robot down into several elements: materials, energy sources, sensors, processors, actuators (the components that execute movements), design, and recyclability.
Each of these elements is assessed against five criteria: resource conservation, lifespan extension, carbon footprint, energy efficiency, and circularity. The results are combined in a weighted matrix to produce an Eco-Score from 0 to 100. The weightings are not fixed at this stage, and defining them will be part of the upcoming research and collaboration work. A low score in one area can signal energy-hungry actuators, limited repairability, hard-to-recycle materials, or the absence of an end-of-life plan. The stated goal is to make environmental trade-offs visible from the earliest stages of design.
Buying the Right-Sized Robot
Sustainability also comes down to purchasing choices. A robot that is larger or more capable than necessary consumes more materials and energy without its capabilities being used. An IEEE RAS-funded team, led by Antun Skuric, developed an open-source platform for assessing the sustainability of collaborative robots. The user defines the required workspace, payload, and trajectory, and the platform identifies the robot with the minimum mass meeting these needs. Interactive tools allow visualization of the robot, observation of the accessible space, and important configurations.
Solar and Pedagogy
In Nigeria, over 90 million people lack reliable access to electricity. The SolarPeer 360 project, led by Umar Adetola Abdulganiyy, a student at the Federal University of Technology in Minna, combines robotic solar tracking, AI-assisted optimization, and peer-to-peer energy distribution. According to the team, “energy captured more efficiently can be shared more equitably.” They report measuring a 60.3% gain in average power in a comparison between a sun-tracking panel and a fixed panel, with power increasing from 3.83 W to 6.14 W. The AI-assisted optimization is said to have reduced energy losses by about 25% in the test environment. Five mini community systems have been deployed, and a solar energy workshop reached over 500 students.
In Cyprus, the Caretta project, led by Mustafa Kemal Ambar, introduced robotics and sustainable development to students aged 8 to 16. Inspired by the loggerhead sea turtle, it gave rise to a robot prototype aimed at reducing coastal pollution. Two coastal cleanup operations were organized, and over 30 students participated in seminars and hands-on activities. During a field exercise, one of them pointed to plastic debris near the water and observed: “Maybe the turtles won’t eat this anymore if Caretta works faster.”
