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This paper addresses adaptive control architectures for systems that respond autonomously to changing tasks. Such systems often have many sensory and motor alternatives and behavior drawn from these produces varying quality solutions. The objective is then to ground behavior in control laws which, combined with resources, enumerate closed-loop behavioral alternatives. Use of such controllers leads to analyzable and predictable composite systems, permitting the construction of abstract behavioral models. Here, discrete event system and reinforcement learning techniques are employed to constrain the behavioral alternatives and to synthesize behavior on-line. To illustrate this, a quadruped robot learning a turning gait subject to safety and kinematic constraints is presented. Keywords: Control Composition, DEDS, Reinforcement Learning, Walking. 1 Introduction Behavior generation in complex sensorimotor systems can be viewed as a scheduling problem in which a policy for engaging resour...

A mobile manipulator in this study is a manipulator mounted on a mobile platform. Assuming the end point of the manipulator is guided , e.g., by a human operator to follow an arbitrary trajectory, it is desirable that the mobile platform is able to move as to position the manipulator in certain preferred configurations. Since the motion of the manipulator is unknown a priori, the platform has to use the measured joint position information of the manipulator for its own motion planning. This paper presents a control algorithm for the platform so that the manipulator is always positioned at the preferred configurations measured by its manipulability. Simulation results are presented to illustrate the efficacy of the algorithm. The algorithm is also implemented and verified on a real mobile manipulator system. The use of the resulting algorithm in a number of applications is also discussed. I. Introduction When a human writes across a board, he positions his arm in a comfortable writin...

geometric constraint analysis, geometric constraint synthesis Dedicated to Lou and Sybil for starting me on this journey, and to Nanny Frieda for reminding me to enjoy the ride. In many areas of science, engineering, medicine, and especially in the field of robotics, there is a need to establish a spatial mapping between two or more 3-dimensional (3-D) shape representations of an object. The registration problem is concerned with finding a spatial transformation which best aligns two object representations. Once this mapping is established, a variety of tasks can be performed using the aligned object representations including modelbased localization, 3-D object recognition, real-time pose tracking and multi-modality sensor fusion. The research goals of this dissertation are the design, implementation and validation of fast and accurate methods for performing 3-D shape-based registration. Fast registration is achieved via speed enhancements to an existing registration method (the iterative closest point algorithm). The implemented enhancements increase registration speeds by a factor of

This paper presents a distributed control approach to legged locomotion that constructs behavior on-line by activating combinations of reusable feedback control laws drawn from a control basis. Sequences of such controller activations result in flexible aperiodic step sequences based on local sensory information. Different tasks are achieved by varying the composition functions over the same basis controllers, rather than by geometric planning of leg placements or the design of new task-specific behaviors. In addition, the deviceindependent nature of the control basis allows its generalization not only over task domains, but also over different hardware platforms. To show the applicability of this approach, a control basis and two generic control gaits for four-legged walking are introduced and tested on an even terrain walking task in an unknown environment. 1 Introduction In order to render a mobile robotic system autonomous it is important to make it capable of traversing various ...

The autonomous operation of robot systems in an uncertain environment poses many challenges to their control architecture. Such systems must be reactive with respect to local disturbances and uncertainties and have to adapt to more persistent changes in environmental conditions and task requirements. In autonomous systems, this adaptation must often occur without outside intervention and within a single trial while avoiding catastrophic failure. This dissertation

Abstract — Recently, [1] suggested to derive tracking controllers for mechanical systems using a generalization of Gauss’ principle of least constraint. This method allows us to reformulate control problems as a special class of optimal control. We take this line of reasoning one step further and demonstrate that well-known and also several novel nonlinear robot control laws can be derived from this generic methodology. We show experimental verifications on a Sarcos Master Arm robot for some of the the derived controllers. We believe that the suggested approach offers a promising unification and simplification of nonlinear control law design for robots obeying rigid body dynamics equations, both with or without external constraints, with over-actuation or underactuation, as well as open-chain and closed-chain kinematics. Index Terms — Non-linear control, robot control, tracking control.

In this thesis, we investigate modeling, control, and coordination of mobile manipulators. A mobile manipulator in this study consists of a robotic manipulator and a mobile platform, with the manipulator being mounted atop the mobile platform. A mobile manipulator combines the dextrous manipulation capability offered by fixed-base manipulators and the mobility offered by mobile platforms. While mobile manipulators offer a tremendous potential for flexible material handling and other tasks, at the same time they bring about a number of challenging issues rather than simply increase the structural complexity. First, combining a manipulator and a platform creates redundancy. Second, a wheeled mobile platform is subject to nonholonomic constraints. Third, there exists dynamic interaction between the manipulator and the mobile platform. Fourth, manipulators and mobile platforms have different bandwidths. Mobile platforms typically have slower dynamic response than manipulators. The objectiv...

The achievement of a wide variety of tasks using a complex system in an unknown environment presents formidable challenges to the control system and its designer. This paper presents a hybrid DEDS approach to the control of such systems which allows for reactivity in the continuous domain and for the automatic generation of the control strategy in the discrete framework, thus drastically reducing the amount of system specification required from the designer. In this framework, control is constructed on-line by activating convergent, reactive controllers in a task dependent fashion. Using certain properties of these control modules and a predicate space characterization of their behavior in terms of their control objectives allows thereby to derive "safe" activation strategies automatically using formal techniques from the DEDS formalism. This, the general, largely device independent character of the underlying control modules, and the absence of a requirement for a monolithic...

... 2003:1783–1800, 2003) suggested to derive tracking controllers for mechanical systems with redundant degrees-offreedom (DOFs) using a generalization of Gauss ’ principle of least constraint. This method allows reformulating control problems as a special class of optimal controllers. In this paper, we take this line of reasoning one step further and demonstrate that several well-known and also novel nonlinear robot control laws can be derived from this generic methodology. We show experimental verifications on a Sarcos Master Arm robot for some of the derived controllers. The suggested approach offers a promising unification and simplification of nonlinear control law design for robots obeying rigid body dynamics equations, both with or without external constraints, with over-actuation or underactuation, as well as open-chain and closed-chain kinematics.