
Northeastern’s Institute for Experiential Robotics
To solve problems of global social relevance through the realization of collaborative, adaptive, ethical, and humanitarian robots and robotic technologies
About the Institute
Application Areas:
- Applications in Biomedical Sciences
- Manufacturing and Automation on the factory floor and in industrial settings
- The development of new sensors and materials for robotics. This includes biometric sensors as well as research on the properties of materials
- The role of Ethics in Robotics as it relates to the Human Robot Interaction
- The use of Robotic technologies in extreme Environment including Space, Polar and Marine.
Area of Interest within Robotics:
- Mathematical Foundations
- Formal Methods
- Manipulation
- Sensors Wearables
- Computer Vision
- Wearable Technologies
- Space, Marine, Polar, Ground
- Robotic Prosthetics and Exoskeletons
- Human Robot Interaction
- Artificial Intelligence / Machine Learning
- Dynamics / Control
- Multirobot systems


Experiential Robotics addresses these interdisciplinary research questions to advance the capabilities of autonomous robots to perform everyday tasks in collaboration with humans
Widespread adoption of autonomous robots in a broad range of human environments relies on robust robot performance and robots’ ability to adapt to uncertainties inherent in everyday human experience, safety protocols, human comfort, and social factors.
IER research is organized into five thrusts:
- Human-robot teaming
- Embodied artificial intelligence
- Systems, design, and control
- Ethics and policy, economics and global frameworks
- Secure and privacy preserving robotics
Interdisciplinary IER teams, in collaboration with our partners, are working on numerous projects with applications from health, sustainability, security, manufacturing and future of work.


Here at the Institute for Experiential Robotics, we envision the following four elements as our guiding principles.
- Measure, Validate, and Improve the Human-Robot Experience
- Robots that can Learn from Human Experience
- Robots that can Learn from Each Other
- Applied and Adopted to Real-World Problems and Human Experience