This paper presents Capabilities2, an advanced skill-based control framework for human-robot interaction (HRI) in ROS2. Capabilities2 enables robots to perform complex tasks by defining and managing skills, which are modular units of functionality. The framework facilitates interoperability, communication, and service management between different components of the robot system, enhancing the robot's ability to interact effectively with humans.

Meet
Kalana Ratnayake
Research Student
Kalana is a PhD candidate at the Faculty of Science and Technology, University of Canberra. He has a background in Computer Science and Engineering. His research interests include robotic navigation and manipulation, human-robot interaction and LLM-based robotic planning. His current research focuses on llm based generative behaviour planning for social robots. His areas of technical experience include ROS1 and ROS2 development (in C++ and Python), Navigation stack and Moveit stacks, robotic planning, and low-level robot control.
As a part of his research work, he develops and maintains the following repositories (some of which might stay hidden until the related publication is out)
As co-collaborator
As the maintainer
- fabric
- fabric_capabilities
- prompt_capabilities
- turtlebot_capabilities
- nav2_capabilities
- moveit2_capabilities
- perception
- perception_capabilities
- supervisor
- experience
- rodeo
- anygrasp_ros
- grasping
- anygrasp_grasping
He also maintains the following stacks for robots used in the lab,
Google Scholar: https://scholar.google.com/citations?hl=en&user=Ujk7jMsAAAAJ