Kuldeep R. Barad

Modular vISion for dynamic grasping of Unknown Resident Space Objects

Advanced robotic capabilities and operational autonomy are crucial enabling technologies for the envisioned progress in in-space servicing, assembly, and manufacturing and resource utilization. Intelligent robotic manipulation is deemed central to enabling and scaling up these applications, where capabilities like handling unknown objects in unstructured scenarios are crucial. In this context, this project proposes to develop a state-of-the-art robot vision pipeline and the underlying algorithms for space-borne vision-based grasping. The project's developments are geared toward testing, validation and use on Redwire's commercial light-weight robotic manipulation system. The development concerns synthesis of compute-efficient pipeline to accomplish the following tasks on an on-board processing unit: (1) accurate estimation of target object’s position and attitude and (2) subsequent estimation of grasp configuration that leads to a secure grasp on an unknown object in space.

Project Information

Duration: 3 + 1 years

Funding Source
FNR Industrial Fellowship
Main Supervisor
Prof. Dr. Miguel Olivares-Mendez
Prof. Dr. Miguel Olivares-Mendez (SnT-UL); Dr. Carol Martinez-Luna (SnT-UL, Co-Supervisor); Dr. Jan Dentler (RedWire Space Europe)
Kuldeep R. Barad
Redwire Space Europe/ Made In Space Europe