An analytical approach to safe collaborative assembly station with cobots

Abstract

Robotics is an interdisciplinary science encompassing vast fields of research: vision, motion planning, control, locomotion, design, and so on. The objective of the creation of robots in the early sixties was to relieve man of certain hard jobs such as: handling a heavy object, and repetitive tasks often tiring or even sometimes infeasible manually. Following this situation, several kinds of manipulators were created . Historically, the manipulator arms were the first manufactured and still are widely used in industry. These robotic systems have the ability to act on the environment through the realization of manipulation tasks such as the grasping of objects, the assembly of pieces, etc. They are nevertheless very limited in their operational workspace and in the type of work they can achieve. New applications where robots are employed near humans are growing rapidly. Unlike industrial robots, which are used in cages to guarantee high precision and safety, collaborative robots, also called Cobots, are designed with a high degree of compliance to ensure safety in presence of humans. Several industrial pick-and-place applications, such as collaborative assembly lines, rely on visual tracking of the parts. Recurrent occlusions caused by the manipulator motion decrease line productivity and can provoke failures. This work provides a complete solution for maintaining an occlusion-free line of sight between a variable-pose camera and the object to be picked by a 6R manipulator that is not wrist-partitioned. We consider potential occlusions by the manipulator as well as the operator working at the assembly station. An actuated camera detects the object goal (part to pick) and keeps track of the operator. The approach consists in using the complete set of solutions obtained from the derivation of the univariate polynomial equation solution to the inverse kinematics (IK). Compared to numerical iterative solving methods, our strategy grants us with a set of joint positions (posture) for each root of the equation from which we extract the best (minimizing the risks of occlusion). Our analytical-based method, integrating collision and occlusion avoidance optimizations, can contribute to greatly enhancing efficiency and safety of collaborative assembly workstations.

Date	21 Dec 2022
Original language	American English
Awarding Institution	École de technologie supérieure
Supervisor	David St-Onge (Supervisor)