Robot safety a top priority
Designing safe, reliable and human-centric robots is a growing priority as they become an integral part of daily life.
Barrier guards, safety fences and motion-sensing alarms used to separate man from machine. But with advances in technology, robots have moved out from factory floors, and into human-centric spaces, from homes to hospitals to hotels.
Issue 04 | January 2025
Collaborative robots, purpose-built to work alongside humans, are increasingly being integrated into sectors grappling with a labour crunch. Singing robot waitstaff deliver bowls of ramen, alleviating the shortage of workers in the food industry; humanoid porters ferry toiletries to hotel rooms, enhancing efficiency and reducing labour costs without compromising the quality of guests’ experience.
As our interactions with robots get more frequent and personal, the quality of these interactions has become a priority. At the Department of Electrical and Computer Engineering, College of Design and Engineering, National University of Singapore, Assistant Professor Fan Shi’s Human-Centred Robotics Lab is driven by one goal: making robot operation as safe as possible in humancentric environments.
Establishing transparency
“I envision a society where everyone can live with joy and dignity,” says Asst Prof Shi. As populations age, we face a growing challenge: there aren’t enough young people to support the daily needs of an increasingly elderly population.”
To address this, Asst Prof Shi believes robots designed to coexist harmoniously with humans are essential. This vision inspired the name of his research group: the Human-Centred Robotics Lab. In the lab, his team develops robots that not only learn and perform tasks but operate safely and reliably in human environments. “Safety and human-centric design lie at the core of our work because robots should enhance lives, not complicate them,” adds Asst Prof Shi.
One of the biggest challenges today is the opaque nature of many state-of-the-art methods, largely due to advancements in deep learning. The advent of foundation models has further complicated this issue, as their complex task dimensions make identifying failure scenarios even more challenging. One of the team’s projects, Diversifying identified failure scenarios to fully address the weak spots of the AIbased robotic systems, tackles this challenge, focusing on creating methodologies that lead to more transparent systems and establishing proper benchmarks to evaluate these AI-based robotic systems.
Issue 04 | January 2025
To do so, Asst Prof Shi’s team is improving the sample efficiency of these AI methods to adapt them to a variety of robotic platforms, all while prioritising safety. These methods have wide-ranging applications, from robotic arms to quadrupedal robots and drones, as these robots are increasingly integrated into our daily environments. Ultimately, he aims to develop a comprehensive approach that serves as a critical benchmark for ensuring the safety and reliability of robots before they are deployed, allowing them to better assist people in real-world settings.
Safety for physical AI
neural-network-controlled quadrupedal
In another project, Systematically evaluating the robotic solution in human-centred environments, Asst Prof Shi’s team aims to make robot operation safer. “When it comes to evaluating the safety of robots in human-centred environments, the first challenge we face is gathering the data needed,” he adds. “To systematically assess safety, we need a wide range of realistic scenarios. However, real-world testing is both dangerous and time-consuming. That’s why we’re focusing on developing more advanced generative methods and high-fidelity simulations to validate these more systems safely and efficiently.”
Currently, his team is working on tackling the problem at its core — by refining the physics models and simulators that underpin these evaluations — as building a robust foundation will ultimately raise the upper limits of what robots can achieve. This will have a significant impact on a wide range of practical applications, from locomotion and drone flight to manipulation tasks — each of which plays a critical role in humancentred settings.
To validate state-of-the-art methods and benchmark their performance, Asst Prof Shi’s team uses various robotic platforms as testbeds, such as the human-like manipulation arms. “Such designs are highly likely to be used in environments where they will coexist with people, and one of our main focuses is on identifying and mitigating potential safety risks, which is an essential aspect of deploying these robots alongside humans,” he adds.
In addition, the team is also exploring the risks associated with AI-based robotic tasks across multiple levels, from foundational models to low-level control systems, which will have broad applicability, spanning various robotic platforms and tasks. “To achieve this, we’re collaborating with domain experts from around the world, combining robotics, simulation and AI expertise to tackle these challenges,” says Asst Prof Shi. “There’s a lot of exciting research in this pipeline, and we look forward to sharing more exciting new results soon this year.”
“Such designs are highly likely to be used in environments where they will coexist with people, and one of our main focuses is on identifying and mitigating potential safety risks, which is an essential aspect of deploying these robots alongside humans.”
CDE brings together world-class researchers across the entire robotics pipeline — from innovative robot hardware design and control theory to artificial intelligence for robotics. “My research complements these efforts by focusing on robust benchmarking and performance evaluation, especially in real-world, humancentred environments,” adds Asst Prof Shi. “The supportive and collaborative environment at CDE has enabled me to build strong partnerships with colleagues and advance impactful robotics research. I look forward to continuing these efforts and contributing to innovation in the field.”