Keyhan Kouhkiloui Babarahmati

Research project title: 
Compliant and Stable Robot Control for Human-Robot Cooperation
Principal goal for project: 
Safe Human-Robot Cooperation/Collaboration/Interaction
Research project: 

It is important to give the robots the capability of moving out of their industrial cages and work in cooperation with humans in a shared-working environment whilst guaranteeing the safety of both humans and robots. In order to achieve this goal, it is essential to make the robots compliant and passive when they come to close interaction with humans/environment. Robots have widespread use in manufacturing where they operate in highly structured environments with minimal and heavily controlled human-robot interaction. They have also been introduced to other industries (e.g.\ health care), which can require more dynamic and interactive tasks that cannot be fully characterized a priori. The impedance controller is a widespread technique enabling robots to interact with uncertain environments within certain boundaries, which defines the relationship between the generated force by the robot and its location in its surrounding environment. This control technique relies on the inverse dynamics modeling to drive the robot to act with an equivalent mechanical impedance or as a Mass-Spring-Damper system, nevertheless, the stability of such systems highly depends on pre-tuned controller gains, which are difficult to obtain for dynamic tasks (e.g.\ polishing, locomotion, etc.). This is more evident in unstructured environments that require adaptive trajectories and/or variable impedance gains. A particular set of tasks to be highlighted are those where uncertain end-effector contact, against other agents or the environment, may occur (e.g.\ polishing, human-robot cooperation, etc.). My main focus and interest are in proposing an approach that guarantees the passivity of the system whilst defining the impedance controller gains variable, which results in making the robot compliant when it comes to human/environment-robot interaction. This controller is capable of dealing with uncertainties in various human/environment-robot interaction scenarios, using the passivity framework to guarantee safety and stability.

Supervisor: 
Student type: 
Aligned student