How Green is Your Robot? New Tools Assess Robotics Sustainability
Robots are increasingly deployed for environmental purposes, such as cleaning rivers, sorting waste, monitoring ecosystems, and inspecting renewable-energy infrastructure. Yet, even the greenest robot carries an environmental burden, from the extraction of rare earth minerals to manufacturing, operation, and disposal. The robotics community has lacked tools to quantify this impact, but new initiatives are emerging.
The Robotics Eco-Label project, led by Bram Vanderborght at Vrije Universiteit Brussel, offers a lightweight web-based toolkit. It breaks down a robot's core technologies into materials, energy sources, sensors, processors, actuators, design, and recyclability. Each aspect is evaluated using five metrics: resource conservation, lifecycle extension, carbon footprint, energy efficiency, and circularity. The scores are combined in a weighted matrix to produce an Eco-Score from 0 to 100. Notably, the weights are not fixed yet, allowing for future refinement.
The toolkit aims to make environmental trade-offs visible early in the development process, enabling sustainable design choices. It also includes educational content and community features so researchers can share case studies and compare methods. For companies, obtaining a high Eco-Score could be a competitive differentiator, while buyers can make more informed decisions.
Another IEEE RAS-funded project, led by Antun Skuric, addresses overspecification—buying robots larger or more capable than needed. An open-source platform allows users to define required workspace, payload, and trajectory, then identifies the minimum-mass robot that meets those requirements. This reduces unused capacity, unnecessary material use, and wasted energy throughout the robot's life cycle. The platform features interactive tools for visualizing robot operations and task constraints.
In Nigeria, the SolarPeer 360 project, led by Umar Adetola Abdulganiyy, tackles energy poverty and inefficient solar energy utilization. It combines robotic solar tracking, AI-assisted optimization, and peer-to-peer energy distribution. Early results showed a 60.3% increase in average power compared to fixed solar panels (from 3.83 W to 6.14 W), and AI-guided advisory reduced energy wastage by about 25% in tests. The team deployed five community mini-systems and conducted a training workshop for over 500 students.
The Caretta project, led by Mustafa Kemal Ambar, brought robotics and sustainability education to students aged 8–16 in Cyprus. Inspired by the Caretta sea turtle, the project developed a functional robot prototype for coastal pollution cleanup. Two clean-up events were held, and over 30 students participated through seminars and hands-on learning. During a field exercise, one student said, "Maybe turtles won’t eat this anymore if Caretta works faster."
These projects, supported by IEEE RAS Sustainability Grants, demonstrate that the robotics community is actively integrating sustainability into research, education, and design. The challenges are both technical and cultural, requiring a shift in how engineers, researchers, and users think about environmental impact. With continued effort, robots can become more sustainable and better support global sustainability goals.