A Hand-Eye-Arm Coordinated System

In this paper we present the description and experiments with a tightly coupled Hand-Eye-Arm manipulatory system. We explain the philosophy and the motivation for building a tightly coupled system that actually consists of very autonomous modules that communicate with each other via a central coordinator. We describe each of the modules in the system and their interactions with each other. We highlight the need for sensory driven manipulation, and explain how the above system, where the hand is equipped with multiple tactile sensors, is capable of both manipulating unknown objects, but also detecting and complying in the case of collisions. We explain the partition of the control of the system into various closed loops, representing coordination both at the level of gross manipulator motions as well as fine motions. We describe the various modes that the system can work in, as well as some of the experiments that are being currently performed using this system

A Robotic Haptic System Architecture

In order to carry out a given task in a unstructured environment, a robotic system must extract physical and geometric properties about the environment and the objects therein. We are interested in the question of what are the necessary elements to integrate a robotics system that would be able to carry out a task, i.e pick-up and transport objects in an unknown environment. One of the major concerns is to insure adequate data throughput and fast communication between modules within the system, so that haptic tasks can be adequately carried out. We also discuss the communication issues involved in the development of such a system

A versatile biomimetic controller for contact tooling and haptic exploration

International audienceThis article presents a versatile controller that enables various contact tooling tasks with minimal prior knowledge of the tooled surface. The controller is derived from results of neuroscience studies that investigated the neural mechanisms utilized by humans to control and learn complex interactions with the environment. We demonstrate here the versatility of this controller in simulations of cutting, drilling and surface exploration tasks, which would normally require different control paradigms. We also present results on the exploration of an unknown surface with a 7-DOF manipulator, where the robot builds a 3D surface map of the surface profile and texture while applying constant force during motion. Our controller provides a unified control framework encompassing behaviors expected from the different specialized control paradigms like position control, force control and impedance control

HEAP: A Sensory Driven Distributed Manipulation System

We address the problems of locating, grasping, and removing one or more unknown objects from a given area. In order to accomplish the task we use HEAP, a system of coordinating the motions of the hand and arm. HEAP also includes a laser range finer, mounted at the end of a PUMA 560, allowing the system to obtain multiple views of the workspace. We obtain volumetric information of the objects we locate by fitting superquadric surfaces on the raw range data. The volumetric information is used to ascertain the best hand configuration to enclose and constrain the object stably. The Penn Hand used to grasp the object, is fitted with 14 tactile sensors to determine the contact area and the normal components of the grasping forces. In addition the hand is used as a sensor to avoid any undesired collisions. The objective in grasping the objects is not to impart arbitrary forces on the object, but instead to be able to grasp a variety of objects using a simple grasping scheme assisted with a volumetric description and force and touch sensing

An Approach to Integrated Tactile Perception

Abstrac

Spatial Position Estimation of Lightweight and Delicate Objects using a Soft haptic Probe

This paper reports on the use of a soft probe as a haptic exploratory device with Force/Moment (F/M) Readings at its base to determine the position of extremely lightweight and delicate objects. The proposed method uses the mathematical relationships between the deformations of the soft probe and the F/M sensor outputs, to reconstruct the shape of the probe and the position of the touched object. The Cosserat rod theory was utilized in this way under the assumption that only one contact point occurs during the exploration and friction effects are negligible. Soft probes in different sizes were designed and fabricated using a Form3 3D printer and Elastic50A resin, for which the effect of gravity is not negligible. Experimental results verified the performance of the proposed method that achieved a position error between of -0.7-13mm, while different external forces (between 0.01N to 1.5N) were applied along the soft probes to resemble the condition of touching lightweight objects. Eventually, the method is used to estimate position of some points in a delicate card house structure

Robotic Haptic Exploration of Shape and Symmetry

This thesis presents research on the use of symmetric models during haptic exploration procedures that have the objective of determining an object’s shape. These haptic exploration techniques, and their subsequent determination of a surface’s geometric properties, are crucial to allow robots to interact with a greater variety of objects, especially as the field of robotics transitions into unstructured environments. Symmetry is an extremely frequent shape property, especially in man-made objects, and it provides shape information that becomes useful in grasping and manipulation tasks, as well as enriching shape information for the aforementioned haptic exploration tasks. In this work, we present an improvement to Gaussian Process-driven exploration tasks. This method allows to describe symmetry to obtain a more precise shape estimation during active exploration, and can even be discovered in real time during the exploration procedure itself. This work involved the creation of a custom software resource to perform Gaussian Process regression with the addition of symmetries, and include a novel method of representing rotational symmetries. These novel models were then used in shape exploration procedures of 2D and 3D surfaces, both in a simulated environment and in an actual robotic task, using a series of custom-made contact sensors. These procedures are able to discover symmetry of each particular object in real time. This property can also be exploited, resulting in shape estimations that have a lower surface error and uncertainty. Additionally, exploration experiments that use these symmetry-finding procedures also require a lower total number of physical contacts and take less time to finish

Emulation of haptic feedback for manual interfaces

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1996.Includes bibliographical references (p. 329-339).by Karon E. MacLean.Ph.D