Predictive Context-Based Adaptive Compliance for Interaction Control of Robot Manipulators

In classical industrial robotics, robots are concealed within structured and well-known environments performing highly-repetitive tasks. In contrast, current robotic applications require more direct interaction with humans, cooperating with them to achieve a common task and entering home scenarios. Above all, robots are leaving the world of certainty to work in dynamically-changing and unstructured environments that might be partially or completely unknown to them. In such environments, controlling the interaction forces that appear when a robot contacts a certain environment (be the environment an object or a person) is of utmost importance. Common sense suggests the need to leave the stiff industrial robots and move towards compliant and adaptive robot manipulators that resemble the properties of their biological counterpart, the human arm. This thesis focuses on creating a higher level of intelligence for active compliance control methods applied to robot manipulators. This work thus proposes an architecture for compliance regulation named Predictive Context-Based Adaptive Compliance (PCAC) which is composed of three main components operating around a 'classical' impedance controller. Inspired by biological systems, the highest-level component is a Bayesian-based context predictor that allows the robot to pre-regulate the arm compliance based on predictions about the context the robot is placed in. The robot can use the information obtained while contacting the environment to update its context predictions and, in case it is necessary, to correct in real time for wrongly predicted contexts. Thus, the predictions are used both for anticipating actions to be taken 'before' proceeding with a task as well as for applying real-time corrective measures 'during' the execution of a in order to ensure a successful performance. Additionally, this thesis investigates a second component to identify the current environment among a set of known environments. This in turn allows the robot to select the proper compliance controller. The third component of the architecture presents the use of neuroevolutionary techniques for selecting the optimal parameters of the interaction controller once a certain environment has been identified

Experiments in cooperative manipulation: A system perspective

In addition to cooperative dynamic control, the system incorporates real time vision feedback, a novel programming technique, and a graphical high level user interface. By focusing on the vertical integration problem, not only these subsystems are examined, but also their interfaces and interactions. The control system implements a multi-level hierarchical structure; the techniques developed for operator input, strategic command, and cooperative dynamic control are presented. At the highest level, a mouse-based graphical user interface allows an operator to direct the activities of the system. Strategic command is provided by a table-driven finite state machine; this methodology provides a powerful yet flexible technique for managing the concurrent system interactions. The dynamic controller implements object impedance control; an extension of Nevill Hogan's impedance control concept to cooperative arm manipulation of a single object. Experimental results are presented, showing the system locating and identifying a moving object catching it, and performing a simple cooperative assembly. Results from dynamic control experiments are also presented, showing the controller's excellent dynamic trajectory tracking performance, while also permitting control of environmental contact force

Ground Robotic Hand Applications for the Space Program study (GRASP)

This document reports on a NASA-STDP effort to address research interests of the NASA Kennedy Space Center (KSC) through a study entitled, Ground Robotic-Hand Applications for the Space Program (GRASP). The primary objective of the GRASP study was to identify beneficial applications of specialized end-effectors and robotic hand devices for automating any ground operations which are performed at the Kennedy Space Center. Thus, operations for expendable vehicles, the Space Shuttle and its components, and all payloads were included in the study. Typical benefits of automating operations, or augmenting human operators performing physical tasks, include: reduced costs; enhanced safety and reliability; and reduced processing turnaround time

Innovative robot hand designs of reduced complexity for dexterous manipulation

This thesis investigates the mechanical design of robot hands to sensibly reduce the system complexity in terms of the number of actuators and sensors, and control needs for performing grasping and in-hand manipulations of unknown objects. Human hands are known to be the most complex, versatile, dexterous manipulators in nature, from being able to operate sophisticated surgery to carry out a wide variety of daily activity tasks (e.g. preparing food, changing cloths, playing instruments, to name some). However, the understanding of why human hands can perform such fascinating tasks still eludes complete comprehension. Since at least the end of the sixteenth century, scientists and engineers have tried to match the sensory and motor functions of the human hand. As a result, many contemporary humanoid and anthropomorphic robot hands have been developed to closely replicate the appearance and dexterity of human hands, in many cases using sophisticated designs that integrate multiple sensors and actuators---which make them prone to error and difficult to operate and control, particularly under uncertainty. In recent years, several simplification approaches and solutions have been proposed to develop more effective and reliable dexterous robot hands. These techniques, which have been based on using underactuated mechanical designs, kinematic synergies, or compliant materials, to name some, have opened up new ways to integrate hardware enhancements to facilitate grasping and dexterous manipulation control and improve reliability and robustness. Following this line of thought, this thesis studies four robot hand hardware aspects for enhancing grasping and manipulation, with a particular focus on dexterous in-hand manipulation. Namely: i) the use of passive soft fingertips; ii) the use of rigid and soft active surfaces in robot fingers; iii) the use of robot hand topologies to create particular in-hand manipulation trajectories; and iv) the decoupling of grasping and in-hand manipulation by introducing a reconfigurable palm. In summary, the findings from this thesis provide important notions for understanding the significance of mechanical and hardware elements in the performance and control of human manipulation. These findings show great potential in developing robust, easily programmable, and economically viable robot hands capable of performing dexterous manipulations under uncertainty, while exhibiting a valuable subset of functions of the human hand.Open Acces

Cooperative impedance control with time-varying stiffness

The focus of much automation research has been to design controllers and robots that safely interact with the environment. One approach is to use impedance control to specify a relationship between a robot\u27s motion and force and control a grasped object\u27s apparent stiffness, damping, and inertia. Conventional impedance control practices have focused on position-based manipulators - which are inherently non-compliant - using constant, task-dependent impedances. In the event of large trajectory tracking errors, this implementation method generates large interaction forces that can damage the workcell. Additionally, these position-based devices require dedicated force/torque sensors to measure and apply forces. In this paper, we present an alternative impedance controller implemented on cooperating torque-based manipulators. Through the use of time-varying impedance parameters, this controller limits the interaction forces to ensure harmless manipulation. Successful completion of transport and insertion tasks demonstrated the effectiveness of the controller

Dual-Arm Generalized Compliant Motion With Shared Control

Dual-Arm Generalized Compliant Motion (DAGCM) primitive computer program implementing improved unified control scheme for two manipulator arms cooperating in task in which both grasp same object. Provides capabilities for autonomous, teleoperation, and shared control of two robot arms. Unifies cooperative dual-arm control with multi-sensor-based task control and makes complete task-control capability available to higher-level task-planning computer system via large set of input parameters used to describe desired force and position trajectories followed by manipulator arms. Some concepts discussed in "A Generalized-Compliant-Motion Primitive" (NPO-18134)

Performance of modified jatropha oil in combination with hexagonal boron nitride particles as a bio-based lubricant for green machining

This study evaluates the machining performance of newly developed modified jatropha oils (MJO1, MJO3 and MJO5), both with and without hexagonal boron nitride (hBN) particles (ranging between 0.05 and 0.5 wt%) during turning of AISI 1045 using minimum quantity lubrication (MQL). The experimental results indicated that, viscosity improved with the increase in MJOs molar ratio and hBN concentration. Excellent tribological behaviours is found to correlated with a better machining performance were achieved by MJO5a with 0.05 wt%. The MJO5a sample showed the lowest values of cutting force, cutting temperature and surface roughness, with a prolonged tool life and less tool wear, qualifying itself to be a potential alternative to the synthetic ester, with regard to the environmental concern

Accomplishing task-invariant assembly strategies by means of an inherently accommodating robot arm

Despite the fact that the main advantage of robot manipulators was always meant to be their flexibility, they have not been applied widely to the assembly of industrial components in situations other than those where hard automation might be used. We identify the two main reasons for this as the 'fragility' of robot operation during tasks that involve contact, and the lack of an appropriate user interface. This thesis describes an attempt to address these problems.We survey the techniques that have been proposed to bring the performance of cur¬ rent industrial robot manipulators in line with expectations, and conclude that the main obstacle in realising a flexible assembly robot that exhibits robust and reliable behaviour is the problem of spatial uncertainty.Based on observations of the performance of position-controlled robot manipulators and what is involved during rigid-body part mating, we propose a model of assembly tasks that exploits the shape invariance of the part geometry across instances of a task. This allows us to escape from the problem of spatial uncertainty because we are 110 longer working in spatial terms. In addition, because the descriptions of assembly tasks that we derive are task-invariant, i.e. they are not dependent on part size or location, they lend themselves naturally to a task-level programming interface, thereby simplifying the process of programming an assembly robot.the process of programming an assembly robot. However, to test this approach empirically requires a manipulator that is able to control the force that it applies, as well as being sensitive to environmental constraints. The inertial properties of standard industrial manipulators preclude them from exhibiting this kind of behaviour. In order to solve this problem we designed and constructed a three degree of freedom, planar, direct-drive arm that is open-loop force-controllable (with respect to its end-point), and inherently accommodating during contact.In order to demonstrate the forgiving nature of operation of our robot arm we imple¬ mented a generic crank turning program that is independent of the geometry of the crank involved, i.e. no knowledge is required of the location or length of the crank. I11 order to demonstrate the viability of our proposed approach to assembly we pro¬ grammed our robot system to perform some representative tasks; the insertion of a peg into a hole, and the rotation of a block into a corner. These programs were tested on parts of various size and material, and in various locations in order to illustrate their invariant nature.We conclude that the problem of spatial uncertainty is in fact an artefact of the fact that current industrial manipulators are designed to be position controlled. The work described in this thesis shows that assembly robots, when appropriately designed, controlled and programmed, can be the reliable and flexible devices they were always meant to be

Impact of end effector technology on telemanipulation performance

Generic requirements for end effector design are briefly summarized as derived from generic functional and operational requirements. Included is a brief summary of terms and definitions related to end effector technology. The second part contains a brief overview of end effector technology work as JPL during the past ten years, with emphasis on the evolution of new mechanical, sensing and control capabilities of end effectors. The third and major part is devoted to the description of current end effector technology. The ongoing work addresses mechanical, sensing and control details with emphasis on mechanical ruggedness, increased resolution in sensing, and close electronic and control integration with overall telemanipulator control system

On Neuromechanical Approaches for the Study of Biological Grasp and Manipulation

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas