Research Topics
Research in our Lab focuses on several key areas related to cyber-physical systems:
Multi-Agent Robotics & Learning
We develop multi-agent reinforcement learning algorithms and cooperative robot behaviors for complex robotic systems. Our research focuses on distributed decision-making, task allocation strategies, and adaptive learning mechanisms that enable robots to work together effectively in dynamic environments. We investigate coordination for warehouse automation, swarm robotics applications, and collaborative manipulation tasks where multiple robots must share resources and coordinate actions to achieve collective objectives. Our work combines theoretical advances in reinforcement learning with practical implementations in real robotic systems, addressing challenges such as communication constraints, partial observability, and scalable coordination in large robot teams.
Bio-Inspired & Soft Robotics
We explore biomimetic approaches to robot learning and design, with particular emphasis on soft robotics and haptic systems for wearable applications. Our research investigates how biological principles can inspire novel robotic mechanisms, cooperation strategies, and sensorimotor integration approaches. We focus on developing compliant robotic systems that can safely interact with humans, studying how sensors and actuators collaborate in soft robotic platforms. We investigate symbiotic relationships between biological principles and robotic systems, exploring how natural coordination mechanisms can inform multi-agent robot behaviors and how bio-inspired algorithms can enhance cooperation in cyber-physical systems.
Human-Robot Interaction
Our research addresses the complex challenges of designing robots that can naturally and effectively interact with humans in diverse social and cultural contexts. We focus on multimodal human-robot communication and socially aware navigation algorithms that respect human social norms. Our work encompasses both technical aspects of HRI (speech recognition, natural language processing, social signal processing) and psychological factors that influence human acceptance and trust in robotic systems. We study group dynamics in human-robot teams and develop methods for robots to adapt their behavior to different cultural contexts and social situations.
Trustworthy AI & Ethics in Robotics
We develop methodologies for creating fair, transparent, and accountable AI systems in robotics applications. Our research addresses the critical need for explainable AI in robotic decision-making, ensuring that autonomous systems can provide clear reasoning for their actions, especially in safety-critical scenarios. We investigate algorithmic fairness in robot behavior, developing techniques to prevent bias and discrimination in robotic systems that interact with diverse human populations. Our work includes designing verification and validation frameworks for AI-enabled robots, establishing metrics for measuring trustworthiness, and creating tools that help developers build more responsible robotic systems. We also explore the ethical implications of autonomous robot deployment and develop guidelines for responsible robotics research and development.
Design Thinking & Future Robotics Systems
We work on merging systems thinking, design thinking, and futures thinking as an integrated framework to design next-generation robotic systems in a more human-centered and sustainable way. This interdisciplinary approach combines traditional engineering methodologies with creative design processes and long-term scenario planning to envision and develop robotic technologies that address future societal needs. Our research includes developing tools and methods for initiating new robotic design concepts, rapid prototyping frameworks for robot development, creative problem-solving approaches for complex robotics challenges, and future scenario planning for robotics deployment. We emphasize participatory design approaches that involve stakeholders in the robotics design process, ensuring that future robotic systems align with human values and societal needs while promoting playful and engaging interactions.
Sustainable & Resilient Robotics
We investigate sustainable and resilient approaches to robotic system design, focusing on creating robots that can operate reliably in challenging environments while minimizing environmental impact throughout their lifecycle. Our research addresses both the sustainability aspects—including energy-efficient algorithms, resource optimization, and environmentally conscious robotics practices—and resilience aspects such as fault tolerance, adaptive behavior under uncertainty, and robust operation in dynamic conditions. We develop embedded control systems that balance performance with energy consumption, investigate renewable energy integration for autonomous mobile robots, and create frameworks for assessing both the environmental impact and operational resilience of robotic deployments. Our work includes developing embedded systems architectures that can adapt to failures and changing conditions, real-time control algorithms that maintain functionality under resource constraints, and methodologies for designing robots that can recover from unexpected situations while maintaining sustainable operation practices.