Object Intelligence for Robots
Project Summary
CynLr invites you to join our development effort. We are open to tailoring the objective of the Internship in line with your skills and interests as we navigate the route to our goal of developing Object Intelligence for Robots. Illustrative opportunities include:
-GPU Accelerated 3D Graph library to replicate features of LabView Graph
-Multi-robot Synchronization including a dynamic safety envelope (using COTS Robots from Kuka/UR)
-Gripper Current based grasp force manipulation
-Determine Part Orientation using Wrist Force/Torque Sensor Data
Qualifications
-Students of Master’s Programmes or those in the last year of a Bachelor’s Programme
-Have taken course-work in a related field (Mechanical, Electronics, Software etc.)
Key Skills
-Good Understanding of basic mathematics and physics
-Ability to work independently as well as collaborate in a multi-disciplinary team
-Able to explore new ideas
-Willingness to work with hardware
CynLr
Know moreToday, even a simple task of putting a screw into a screw hole without slipping a thread remains non-automatable across the globe. Imagine what it would take for a robot to assemble a Smartphone or a car (Elon Musk’s words) by putting together 1000s of parts of varied shapes and weights presented in random orientations. Enabling robots to perform Picking Orienting and Placing of objects straight from its container has been a long-standing unsolved problem – touted as The Holy Grail of Robotics.
We at CynLr build the missing pieces of Visual Intelligence for Robotic Arms to make them Object aware to manipulate with superior agility - adapting to the varying shapes, orientations, and weights of the object. This we envision could simplify and standardize large, customized factory lines into LEGO blocks of micro-factories.
