Towards Easing Automation of Robotic Kitting Operations

This paper proposes a framework to make the robot programming faster, user-friendly, and flexible for kitting operations. This is achieved by innovating at three different levels; (i) at the motion stack level, it integrates the robot with a constraint-based robot programming paradigm in which a novel approach for obstacle avoidance is introduced, (ii) at the discrete planning level, it introduces adaptive planning to derive an optimal sequence of robot kitting operations, (iii) and at the knowledge representation level, the overall operation is aided by a world-model that formally represents and provides services from the knowledge of the task, the robot state, and the sensor data. The framework provides industrially relevant capabilities like, collision avoidance independent of the obstacle location, optimal discrete planning of the actions based on the costs and goals, and dealing with complex conditions such as object blocking and object graspability. The performance of the proposed framework is evaluated through a set of experiments.