This paper presents an overview of a newly developed Coupled Layer Architecture for Robotic Autonomy (CLARAty), which is designed for improving the modularity of system software while more tightly coupling the interaction of autonomy and controls. First, we frame the problem by briefly reviewing previous work in the field and describing the impediments and constraints that been encountered. Then we describe why a fresh approach of the topic is warranted, and introduce our new two-tiered design as an evolutionary modification of the conventional three-level robotics architecture. The new design features a tight coupling of the planner and executive in one Decision Layer, which interacts with a separate Functional Layer at all levels of system granularity. The Functional Layer is an object-oriented software hierarchy that provides basic capabilities of system operation, resource prediction, state estimation, and status reporting. The Decision Layer utilizes these capabilities of the Func...

This paper presents a new model-based adaptive controller and proof of its global asymptotic stability with respect to the standard rigid body model of robot arm dynamics. Experimental data from a study of one new and several established globally asymptotically stable adaptive controllers on two very different robot arms (i) demonstrates the superior tracking performance afforded by the model-based algorithms over conventional PD control, (ii) demonstrates and compares the superior performance of adaptive model-based algorithms over their non-adaptive counterparts, (iii) reconciles several previous contrasting empirical studies, and (iv) examines contexts which compromise their advantage.

This paper discusses computational and experimental details necessary for successfully implementing and evaluating a wide variety of force control strategies. First, a review of both explicit force and impedance control strategies is provided. Second, the basic computational requirements of these schemes are discussed, and the hardware and timing information for our implementation is provided. Third, computational problems such as noise filtering and sampling rates are explained and discussed in detail. Finally, a review of the experimental results obtained is provided. These results support the previous discussions by demonstrating the importance of fully considering the implementational details required for successful force control of robotic manipulators.

This paper discusses the essential equivalence of second order impedance control with force feedback and proportional gain explicit force control with force feedforward. This is first done analytically by reviewing each control method and showing how they mathematically correspond for constrained manipulator control. For stiff environments the correspondence is exact. However, even for softer environments similar response of the system is indicated. Next, the results of an implementation of these control schemes on the CMU DD Arm II are presented, confirming the predictions of the analysis. These results experimentally demonstrate that proportional gain force control and impedance control, with and without dynamics compensation, have equivalent response to commanded force trajectories. 1 Introduction There is a whole class of tasks that implicitly require controlling the force of interaction between a manipulator and its environment: pushing, scraping, grinding, pounding, polishing, t...

The use of two arms simplifies manipulatory tasks such as assembly of an object from large parts which cannot be handled by one arm. This paper describes the control method for coordination of two arms. As fundamental tasks, the parallel transfer task and the rotational transfer task are considered. More complex tasks are accomplished by using these two modes simultaneously. The control of motor torque of each joint is adopted instead of joint position control. The wrist force sensor is used in order to measure the interactive force between two arms.

This paper reports comparative experiments with a provably correct model-based adaptive robot control algorithm for simultaneous position and force trajectory tracking of a robot arm whose gripper is in point contact with a smooth surface. The experiments show the new adaptive modelbased o#ers performance superior to that of its non-modelbased counterpart over a wide variety of operating conditions.

This report presents an overview of a newly developed robotics architecture for improving the modularity of system software while more tightly coupling the interaction of autonomy and controls within the system. To accomplish this, we have modified the conventional three-level robotics architecture with separate and distinct functional, executive, and planning capabilities, into a new two-layer design. This design features a tight coupling of the planner and executive in one Decision Layer, which interacts with a separate Functional Layer at all levels of system granularity. The Functional Layer is an interface to all system hardware and its capabilities. It has a number of specific characteristics. First and foremost it is an object-oriented hierarchy which captures granularity and abstraction of the system. Second, the state of all system parts is contained in the appropriate objects and obtained from them by query. This includes state variable values, object state machine status, resource usage, health monitoring, etc. Third, all objects have basic encoded functionality for themselves, accessible from within the Functional Layer, as well as the Decision Layer. Fourth, all objects may have local planners, such as those used for arm motion or driving. Fifth, objects have resource usage predictors, providing estimates of future resource usage to specified levels of fidelity, where high levels may require access to subordinate

In this paper we discuss different control design methods for nonlinear control systems. We focus our attention on passivity-based control and the feedback linearization approach for solving set-point and tracking control problems. We also consider the case of model and parameter uncertainties. We concentrate on Euler-Lagrange systems which is a fairly wide and illustrative class of nonlinear systems and which includes a large number of physical systems, in particular we approach the output feedback control problem of EL systems. Some comments on other feedback linearizable systems are given. Keywords. Nonlinear control, feedback linearization, Euler-Lagrange systems, passivity, observers, robust control. 2 A basic problem in control theory may be described as follows: given a plant, design a control mechanism in such a way that the plant together with the controller meets certain design specifications. The above regulation problem arises in numerous situations, for instanc...