Motion and Force Planning for Manipulating Heavy Objects by Pivoting

Manipulation of objects by exploiting their contact with the environment can enhance both the dexterity and payload capability of robotic manipulators. A common way to manipulate heavy objects beyond the payload capability of a robot is to use a sequence of pivoting motions, wherein, an object is moved while some contact points between the object and a support surface are kept fixed. The goal of this paper is to develop an algorithmic approach for automated plan generation for object manipulation with a sequence of pivoting motions. A plan for manipulating a heavy object consists of a sequence of joint angles of the manipulator, the corresponding object poses, as well as the joint torques required to move the object. The constraint of maintaining object contact with the ground during manipulation results in nonlinear constraints in the configuration space of the robot, which is challenging for motion planning algorithms. Exploiting the fact that pivoting motion corresponds to movements in a subgroup of the group of rigid body motions, SE(3), we present a novel task-space based planning approach for computing a motion plan for both the manipulator and the object while satisfying contact constraints. We also combine our motion planning algorithm with a grasping force synthesis algorithm to ensure that friction constraints at the contacts and actuator torque constraints are satisfied. We present simulation results with a dual-armed Baxter robot to demonstrate our approach.

I. Introduction

Manipulation of heavy and bulky objects is a challenging task for manipulators and humanoid robots. An object is considered heavy if the manipulator’s joint torques are not large enough to balance the object’s weight while lifting it off the ground. Thus, heavy objects cannot be manipulated with the usual pick-and-place strategy due to actuator saturation. Consider the manipulation scenario shown in Fig. 1, where a heavy object has to be moved from an initial pose to a final pose by a dual-armed robot. The object has to negotiate a step during the manipulation which implies that the final pose cannot be achieved by either pick-and-place strategies or by pushing. One possible way to move the object and negotiate the step is to use a sequence of pivoting motions, which we call object gaiting. Object gaiting is a common strategy used by humans to manipulate heavy objects. Therefore, the goal of this paper is to develop an algorithmic approach to compute a plan for manipulating heavy objects by a sequence of pivoting motions.