Description:

This project builds up the skill of impact aware non prehensile manipulation through a hitting motion by allowing the robot arm to come in contact with the environment with parts other than its end effector. In tasks where directional effective inertia of a robot is important at the contact point, it is useful to understand inertia not just at the end effector of the robot but also at other points of the robot. Hitting with other joints allows us to manipulate heavier objects since the robot effective inertia is higher at joints other than its end effector. We propose a methodology for selecting a hitting joint based on the hitting task requirements, impact posture generation for the robot and a smooth generation of desired directional inertia values through a hitting motion.

Description:

This paper presents a data collection framework and a learning model to understand the motion of an object after being subject to an impulse. The data collection framework consists of an automated dual arm setup hitting an object to each other, like a collaborative air-hockey game. The design of the system is further detailed in the system. An impact aware extended Kalman filter is proposed for automation of the air-hockey setup which approximates the discontinuous impulse motion equations through a hitting force model by balancing the energies during collision. To capture the variance in the motion that stochasticity of friction introduces, the errors in the controls for the hitting flux, we model the stochastic relationship between hitting impulse and object's resulting displacement, using full density modeling. Further we show the application of the learnt motion model for planning sequential hits with two or more robots, in a Golf-like principle, to let an object reach a location far beyond reach of any single robot.

Description:

In this article, we propose a metric called hitting flux, which is used in the motion generation and controls for a robot manipulator to interact with the environment through a hitting or a striking motion. Given the task of placing a known object outside of the workspace of the robot, the robot needs to come in contact with it at a nonzero relative speed. The configuration of the robot and the speed at contact matter because they affect the motion of the object. The physical quantity called hitting flux depends on the robot's configuration, the robot speed, and the properties of the environment. An approach to achieve the desired directional preimpact flux for the robot through a combination of a dynamical system for motion generation and a control system that regulates the directional inertia of the robot is presented. Furthermore, a quadratic program formulation for achieving a desired inertia matrix at a desired position while following a motion plan constrained to the robot limits is presented. The system is tested for different scenarios in simulation showing the repeatability of the procedure and in real scenarios with KUKA LBR iiwa 7 robot.

Description:

This paper proposes a manipulation scheme based on learning the motion of objects after being hit by a robotic end-effector. This allows for the object to be positioned at a desired location outside the physical workspace of the robot. An estimate of the object dynamics under friction and collisions is learnt and used to predict the desired hitting parameters (speed and direction), given the initial and desired location of the object. Based on the obtained hitting parameters, the desired pre-impact velocity of the end-effector is generated using a stable dynamical system. The performance of the proposed DS is validated in simulation and and is used to learn a model for hitting using real robot. The approach is tested on real robot with a KUKA LBR IIWA robot.