Intelligence and Mobility Synthesis

The Intelligence and Mobility Synthesis group advances research at the intersection of robotics, autonomy, and human-centered systems, with a focus on enabling safe, efficient, and trustworthy interaction between humans and intelligent machines. Our work spans a broad spectrum of robotic platforms and applications, including autonomous vehicles, wearable and assistive robots, origami-inspired robotic systems, and human–robot interaction. A central theme of our research is the integration of machine learning and artificial intelligence with control and decision-making frameworks to create systems that can adapt to complex, dynamic environments while maintaining performance guarantees.

Research Focus

A key research focus is human-centered autonomy, where we develop quantitative models of human trust, decision-making under risk, and behavioral biases. These models inform the design of trust-aware and regret-aware control strategies, motion planning algorithms, and decision-making frameworks that explicitly account for both system-level safety and efficiency as well as human satisfaction and collaboration quality.

In parallel, we investigate energy-efficient and connected mobility systems, particularly in the context of connected and automated vehicles, where data-driven and control-based approaches are used to optimize driving performance and reduce energy consumption.

Another major thrust is human–robot collaboration and interface design, which includes the development of intuitive human–machine interfaces and cooperative robotic systems that enhance usability, transparency, and real-time interaction. Together, these efforts aim to enable seamless integration of intelligent robotic systems into human environments.

Energy Efficient Driving With Connected and Automated Vehicles (Vahidi)

Human-Robot Collaboration Systems (Wagner)

Design of Human-Machine Interfaces (Wang)