Non-Prehensile Object Transportation via Model Predictive Non-Sliding Manipulation Control

This article proposes a model predictive non-sliding manipulation (MPNSM) control approach to safely transport an object on a tray-like end-effector of a robotic manipulator. For the considered non-prehensile transportation task to succeed, both non-sliding manipulation and the robotic system constraints must always be satisfied. To tackle this problem, we devise a model predictive controller enforcing sticking contacts, i.e., preventing sliding between the object and the tray, and assuring that physical limits such as extreme joint positions, velocities, and input torques are never exceeded. The combined dynamic model of the physical system, comprising the manipulator and the object in contact, is derived in a compact form. The associated non-sliding manipulation constraint is formulated such that the parametrized contact forces belong to a conservatively approximated friction cone space. This constraint is enforced by the proposed MPNSM controller, formulated as an optimal control problem that optimizes the objective of tracking the desired trajectory while always satisfying both manipulation and robotic system constraints. We validate our approach by showing extensive dynamic simulations using a torque-controlled 7-degree-of-freedom (DoF) KUKA LBR IIWA robotic manipulator. Finally, demonstrative results from real experiments conducted on a 21-DoF humanoid robotic platform are shown

Control of sliding velocity in robotic object pivoting based on tactile sensing

Control of robots manipulating objects using only the sense of touch is a challenge. In-hand motion of the manipulated object highly depends on the friction forces acting at the contact surfaces. Soft contacts allow torsional frictions as well as friction forces, therefore robots can perform more complex manipulation abilities, like object pivoting. Control of the pivoting sliding motion is very difficult especially without any visual feedback. The paper proposes a novel method to control the sliding velocity of the object by using a simple parallel gripper endowed with force/tactile sensors only. The strategy is based on a nonlinear observer that estimates the sliding velocity from force/torque measurements and a model of the sliding dynamics

Hybrid motion planning approach for robot dexterous hands

This paper presents a manipulation planning approach for robot hands that enables the generation of finger trajectories. The planner is based on a hybrid approach that combines discrete-continuous kinematics using a fully discrete transition system. One of the main contributions of this work consists in the representation of the universe of different submodel combinations, as states in a discrete transition system. The manipulated object geometry is taken into account and the system composed by the object and the hand is modeled as a set of closed kinematical chains. The methodology enables the synthesis of complex manipulation trajectories, when one or more fingers change the contact condition with the object. Contact condition changes include rolling contact, sliding contact, contact loss and contact establishment. Tests were carried out employing a three finger manipulation task in computer simulations and with an experimental setup

Visual Servoing and Robust Object Manipulation Using Symmetries and Conformal Geometric Algebra

Object tracking and manipulation is an important process for many applications in robotics and computer vision. A novel 3D pose estimation of objects using reflectionally symmetry formulated in Conformal Geometric Algebra (CGA) is proposed in this work. The synthesis of the kinematics model for robots and a sliding mode controller using the CGA approach is described. Real time implementation results are presented for the pose estimation of object using a stereo vision system.ITESO, A.C.CINVESTA

Models for pushing objects with a mobile robot using single point contact

In many mobile robotic manipulation tasks it is desirable to interact with the robots surroundings without actually grasping the object being manipulated. Non-prehensile manipulation allows a robot to interact in situations which would otherwise be impossible due to size or weight. This paper presents the derivation of a mathematical model of an object pushed by a single point and sliding in the presence of friction where the dynamic effects of mass and inertia are significant. This model is validated using numerical simulation. The derived dynamic model is also compared with a kinematic approximation from literature, showing that under certain conditions, the motion of a pushed object is similar to the motion of a non-holonomic vehicle. Finally, the results of experimental investigations are discussed and promising directions for further work are proposed. ©2010 IEEE

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

The GR2 gripper: an underactuated hand for open-loop in-hand planar manipulation

Performing dexterous manipulation of unknown objects with robot grippers without using high-fidelity contact sensors, active/sliding surfaces, or a priori workspace exploration is still an open problem in robot manipulation and a necessity for many robotics applications. In this paper, we present a two-fingered gripper topology that enables an enhanced predefined in-hand manipulation primitive controlled without knowing the size, shape, or other particularities of the grasped object. The in-hand manipulation behavior, namely, the planar manipulation of the grasped body, is predefined thanks to a simple hybrid low-level control scheme and has an increased range of motion due to the introduction of an elastic pivot joint between the two fingers. Experimental results with a prototype clearly show the advantages and benefits of the proposed concept. Given the generality of the topology and in-hand manipulation principle, researchers and designers working on multiple areas of robotics can benefit from the findings