Dr Chapa Pelendage
- Marie Sklodowska-Curie Future Roads Fellow
- Assistant Professor/Lecturer in Assistive Robotics, University of Bristol
About
Dr Chapa Sirithunge received her bachelor’s and PhD in Electrical Engineering from the University of Moratuwa, Sri Lanka. During her PhD, she developed cognitive frameworks for socially interactive robots in domestic and social domains. Upon graduation, she joined the Department of Computer Science and Engineering, University of Moratuwa as a visiting lecturer in 2020. She then served as a lecturer at the Sri Lanka Technological Campus until she joined the University of Cambridge as a postdoctoral researcher. She was a member of the Bio-inspired Robotics lab where she explored how soft robotics could be used in human-robot interaction and in 2023 she won the prestigious Marie Curie FutureRoads fellowship to continue her research in Robotics in a Civil Engineering domain to improve roads in the future. In the FutureRoads project, she is developing a multi-agent system based on sensor fusion to improve the safety of heavy machines and workers. She further develops simulations to represent situation-aware human-machine collaborative systems in this context. Her research interests include bio-inspired robots, cognitive robotics, soft robots, and collaborative AI.
Fellowship period: 15 June 2023 – 31 May 2026
Research
Research Project: A Multi-Agent System for Heavy Machine Operation through Context-Aware Sensor Fusion
Abstract:
Construction sites in the UK remain hazardous, responsible for over 20% of workplace fatalities. These incidents result not only in tragic loss of life but also in significant financial costs due to equipment damage and compensation claims. A key factor in many accidents is the limited situational awareness of heavy machinery operators and workers. There is a critical need to integrate Robotics, and Automation to improve safety on these sites, especially where automation is challenging due to the complexity and variability of the environment.
This project follows a three-stage approach to develop a smart, adaptable safety system for construction.
First, the project will identify specific safety requirements for construction workers by analysing common site hazards. Based on this, a digital interface will be developed, enabling workers to monitor risks in real-time. Next, an intelligent algorithm will allow the system to interpret construction site activity as work proceeds, enhancing its ability to anticipate risks and respond to dynamic changes. Finally, visual and audio alerts will be incorporated to deliver immediate feedback on hazards, making the system practical for high-traffic, limited-visibility areas.
Field testing will help refine this technology to address the unique safety needs of construction environments. Unlike manufacturing, where robotic systems are well-integrated, this project represents one of the first targeted applications of robotics for safety on construction sites. Once successful, this solution can transform industry practices, contributing to sustainable, resilient infrastructure and aligning with SDGs focused on safety, innovation, and sustainable cities.
Upon completion, this research will be deployed as a human-machine interface in work environments, control rooms, and on heavy machinery as a real-time tool to observe otherwise hidden areas, anticipate hazards, and help avoid them—all without replacing human oversight. The system’s modular design will enable it to be adapted to different work sites.
This research establishes a smart interface between workers and machines, combining robotics and algorithms to manage complex, dynamic environments. For instance, if a machine operator needs an overview of a distant area, they can request a robot to capture a real-time image, ensuring safer conditions. Additionally, algorithms will support machine-to-machine communication, creating a network of "talking machines" that share critical information. Concepts like reinforcement learning, self-organisation, and embodied intelligence will make this a robust, responsive safety system.
Current Progress: Development has reached the simulation stage, involving heavy machinery, sensorized environments, multi-agent system (MAS) algorithms, and human factors such as emotions that could serve as cues to prevent hazards. Currently, the fellow is seeking an industry secondment to observe worker interactions with these systems, evaluate the feasibility of using robots in dynamic settings like construction and test the simulations in real world. Addressing these human-centred requirements will strengthen the system’s integration and adaptability, ensuring a safe, collaborative, and practical solution for real-world applications.