Prehensile Pushing: In-hand Manipulation with Push-Primitives

This paper explores the manipulation of a grasped object by pushing it against its environment. Relying on precise arm motions and detailed models of frictional contact, prehensile pushing enables dexterous manipulation with simple manipulators, such as those currently available in industrial settings, and those likely affordable by service and field robots. This paper is concerned with the mechanics of the forceful interaction between a gripper, a grasped object, and its environment. In particular, we describe the quasi-dynamic motion of an object held by a set of point, line, or planar rigid frictional contacts and forced by an external pusher (the environment). Our model predicts the force required by the external pusher to “break” the equilibrium of the grasp and estimates the instantaneous motion of the object in the grasp. It also captures interesting behaviors such as the constraining effect of line or planar contacts and the guiding effect of the pusher’s motion on the objects’s motion. We evaluate the algorithm with three primitive prehensile pushing actions—straight sliding, pivoting, and rolling—with the potential to combine into a broader in-hand manipulation capability.National Science Foundation (U.S.). National Robotics Initiative (Award NSF-IIS-1427050)Karl Chang Innovation Fund Awar

A two-phase gripper to reorient and grasp

This paper introduces the design of novel two-phase fingers to passively reorient objects while picking them up. Two-phase refers to a change in the finger-object contact geometry, from a free spinning point contact to a firm multipoint contact, as the gripping force increases. We exploit the two phases to passively reorient prismatic objects from a horizontal resting pose to an upright secure grasp. This problem is particularly relevant to industrial assembly applications where parts often are presented lying on trays or conveyor belts and need to be assembled vertically. Each two-phase finger is composed of a small hard contact point attached to an elastic strip mounted over a V-groove cavity. When grasped between two parallel fingers with low gripping force, the object pivots about the axis between the contact points on the strips, and aligns upright with gravity. A subsequent increase in the gripping force makes the elastic strips recede into the cavities letting the part seat in the V-grooves to secure the grasp. The design is compatible with any type of parallel-jaw gripper, and can be reconfigured to specific objects by changing the geometry of the cavity. The two-phase gripper provides robots with the capability to accurately position and manipulate parts, reducing the need for dedicated part feeders or time-demanding regrasp procedures.National Science Foundation (U.S.). National Robotics Initiative (NSF-IIS-1427050

Dexterous manipulation with simple grippers

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, May, 2020Cataloged from the official PDF of thesis.Includes bibliographical references (pages 117-124).This thesis focuses on enabling robots, specially those with simple grippers, to dexterously manipulate an object in a grasp. The dexterity of a robot is not limited to the intrinsic capability of a gripper. The robot can roll the object in the gripper using gravity, or adjust the object's pose by pressing it against a surface, or it can even toss the object in the air and catch it in a different pose. All these techniques rely on resources extrinsic to the hand, either gravity, external contacts or dynamic arm motions. We refer to such techniques collectively as "extrinsic dexterity". We focus on empowering robots to autonomously reason about using extrinsic dexterity, particularly, pushes against external contacts. We develop mechanics and algorithms for simulating, planning, and controlling motions of an object pushed in a grasp. We show that the force-motion relationship at contacts can be captured well with complementarity constraints and the mechanics of prehensile pushing in a general setting can be formulated as a mixed nonlinear complementarity problem. For computational efficiency, we derive the abstraction of the mechanics in the form of motion cones. A motion cone defines the set of object motions a pusher can induce using frictional contact. Building upon these mechanics models, we develop a sampling-based planner and an MPC-based controller for in-hand manipulation. The planner generates a series of pushes, possibly from different sides of the object, to move the object to a desired grasp. The controller generates local corrective pushes to keep the object close to the planned pushing strategy. With a variety of regrasp examples, we demonstrate that our planner-controller framework allows the robot to handle uncertainty in physical parameters and external disturbances during manipulation to successfully move the object to a desired grasp.by Nikhil Chavan-Dafle.Ph. D.Ph.D. Massachusetts Institute of Technology, Department of Mechanical Engineerin

Regrasping by Fixtureless Fixturing

This paper presents a fixturing strategy for re-grasping that does not require a physical fixture. To regrasp an object in a gripper, a robot pushes the object against external contact/s in the environment such that the external contact keeps the object stationary while the fingers slide over the object. We call this manipulation technique fixtureless fixturing. Exploiting the mechanics of pushing, we characterize a convex polyhedral set of pushes that results in fixtureless fixturing. These pushes are robust against uncertainty in the object inertia, grasping force, and the friction at the contacts. We propose a sampling-based planner that uses the sets of robust pushes to rapidly build a tree of reachable grasps. A path in this tree is a pushing strategy, possibly involving pushes from different sides, to regrasp the object. We demonstrate the experimental validity and robustness of the proposed manipulation technique with different regrasp examples on a manipulation platform. Such fast and flexible regrasp planner facilitates versatile and flexible automation solutions

Experimental Validation of Contact Dynamics for In-Hand Manipulation

This paper evaluates state-of-the-art contact models at predicting the motions and forces involved in simple in-hand robotic manipulations. In particular it focuses on three primitive actions—linear sliding, pivoting, and rolling—that involve contacts between a gripper, a rigid object, and their environment. The evaluation is done through thousands of controlled experiments designed to capture the motion of object and gripper, and all contact forces and torques at 250 Hz. We demonstrate that a contact modeling approach based on Coulomb’s friction law and maximum energy principle is effective at reasoning about interaction to first order, but limited for making accurate predictions. We attribute the major limitations to (1) the non-uniqueness of force resolution inherent to grasps with multiple hard contacts of complex geometries, (2) unmodeled dynamics due to contact compliance, and (3) unmodeled geometries due to manufacturing defects. Keywords: Contact Force, Contact Model, Grasp Object, Contact Compliance, Grip Force Increas