Sharif Digital Repository

In recent years, a number of new heuristic search methods have been developed in the field of automated planning. Enforced hill climbing (EHC) is one such method which has been frequently used in a number of AI planning systems. Despite certain weaknesses, such as getting trapped in dead-ends in some domains, this method is more competitive than several other methods in many planning domains. In order to enhance the efficiency of ordinary enforced hill climbing, a new form of enforced hill climbing, called guided enforced hill climbing, is introduced in this paper. An adaptive branch ordering function is the main feature that guided enforced hill climbing has added to EHC. Guided enforced... 

Self-reconfigurable modular robots (SRMRs) have recently attracted considerable attention because of their numerous potential applications in the real world. In this paper, we draw a comprehensive comparison among five different algorithms in path planning of a novel SRMR system called ACMoD through an environment comprised of various terrains in a static condition. The contribution of this work is that the reconfiguration ability of ACMoD has been taken into account. This consideration, though raises new algorithmic challenges, equips the robot with new capability to pass difficult terrains rather than bypassing them, and consequently the robot can achieve better performance in terms of... 

Morphological computation (MC) has revolutionized robotic systems employing morphological properties (MP). Thus far, morphology has been mostly used to analyze morphological functionalities qualitatively after design phase of robotic systems. Furthermore, morphology has verified qualitative requirements, not modeled quantitative specifications. To fill this gap, we present a distributed algorithm to monitor module reconfiguration for homogeneous self-reconfigurable robots (HSRs) considering the size of modules. In this method, neighboring modules of a particular module occupy a spatial region called adjacency configuration (AC), whose size depends on the module size; then, we monitor... 

Enforced hill climbing (EHC), a heuristicaa search method, has been frequently used in a number of AI planning systems. This paper presents a new form of EHC, guided enforced hill climbing (GEHC), to enhance EHC efficiency. Main feature in GEHC is an adaptive ordering function. GEHC has shown a significant improvement in EHC efficiency, especially when applied to larger problems  

Featuring a nonlinear novel design, Gimbal transmission, is a replacement for traditional robotic joints like gearboxes and revolute joints. This mechanism is one of the most recent types of nonlinear direct transmission (DT) methods in robots. As an alternative for traditional drive methodologies - herein called direct drive transmission (DD) methods, DT provides dynamic coupling and joint interaction attenuation while its capability to be adjusted for a desired task space point, smooth input-output characteristic, and varying reduction ratio lead to a desired force and motion behavior for the whole manipulator. In this paper, design optimization of a gimbal mechanism used as a replacement... 

In this paper, we introduce a new approach to fault detection and isolation for robot manipulators. Our technique is based on using a new simplified Euler-Lagrange (EL) equation that reduces complexity of the proposed fault detection method. The proposed approach isolates the faults and is capable of handling the uncertainty in manipulator gravity vector. It is shown that the effect of uncalibrated torque sensor measurement is asymptotically rejected in the detection process. A simulation example is presented to illustrate the results. © 2009 IEEE  

In this paper, we introduce DiFF, a novel extension of the Fast Forward (FF) planning system. FF is a domain independent planner that employs a forward heuristic search. Its search strategy is an enforced form of hill climbing. In order to move to a more promising state, FF evaluates successor states without any particular order. In this paper, we introduce a new form of the enforced hill climbing, which we call directed enforced hill climbing, to enhance the efficiency of Fast Forward planning. This strategy evaluates successor states in the order recommended by an adaptive heuristic function. Our experimental results in several planning domains show a significant improvement in the... 

In this paper, a nonlinear adaptive impedance controller is proposed for UAVs equipped with a robot manipulator that interacts with environment. In this adaptive controller, by considering the nonlinear dynamics model of the UAV plus the robot manipulator in Cartesian coordinates, all of model parameters are considered to be completely uncertain and their estimation is updated using an adaptation law. The objective of the proposed adaptive controller is the control of manipulator's end-effector impedance in Cartesian coordinates to have a stable physical interaction. The adjustable Cartesian impedance is a desired dynamical relationship between the end-effector motion in Cartesian... 

In this paper, a decentralized controller for trajectory tracking of modular and reconfigurable robot manipulators is developed. The proposed control scheme uses joint-torque sensory feedback; also sliding mode control is employed to make both position and velocity tracking errors of robot manipulators globally converging to zero. Proposed scheme also guarantees that all signals in closed-loop systems will be bounded. In contrast to some of prior works in this scheme, each controller uses a smooth law to achieve its purposes. In this method, each controller uses only local information for producing control law hence separated controller can be used to control each module of manipulator and... 

In this paper, a new nonlinear robust adaptive impedance controller is addressed for Unmanned Aerial Vehicles (UAVs) equipped with a robot manipulator that physically interacts with environment. A UAV equipped with a robot manipulator is a novel system that can perform different tasks instead of human being in dangerous and/or inaccessible environments. The objective of the proposed robust adaptive controller is control of the UAV and its robotic manipulators end-effector impedance in Cartesian space in order to have a stable physical interaction with environment. The proposed controller is robust against parametric uncertainties in the nonlinear dynamics model of the UAV and the robot... 

In this paper, a new fuzzy based Model Coordination (F-MC) strategy is proposed for hierarchical control of large-scale systems (LSS). To solve the overall problem with a two-level optimal control strategy, we first decompose the system into several sub-systems at the first level. Then, at the second level, a fuzzy coordinator will be used to predict the interaction between subsystems. The proposed fuzzy based coordination approach is applicable to all types of LSS. Although in this paper, an optimal control of a 2DOF robot manipulator, as a LSS, will be considered. The obtained results are compared with the centralized optimization  

This paper presents a fuzzy-based interaction prediction approach (F-IPA) for two-level optimal control of large-scale systems. The design procedure uses a decomposition/coordination framework of hierarchical structures. At the first level, the system is decomposed into subsystems for which subproblems are formed. At the second level, a fuzzy coordinator is used to predict the coordination parameters needed to coordinate the solutions of the first level subproblems. The fuzzy coordinator uses a critic vector to evaluate its performance and learn its parameters by minimizing an energy function. The proposed control scheme is implemented on a two-degrees-of-freedom (2DOF) model of robot... 

Many real-time systems are in fact isochronal, where both early and late responses are harmful to the system or lead to lower quality of service. Real-time task scheduling problems proved that are NP-hard problems. Therefore, it is necessary to apply a heuristic search strategy on these problems. In this paper, a multi-objective genetic algorithm is proposed for static task scheduling in non-overloaded isochronal soft real-time systems. Its objective is to maximize the total utility of jobs. Simulation results indicate that genetic algorithm could be a suitable heuristic search strategy for task scheduling in isochronal soft real-time systems. © 2009 IEEE  

We present a method for global estimation of joint velocities in rigid manipulators. A class of velocity observers with smooth dynamics are introduced whose structure depend on freely selectable functions and gains giving the flexibility of achieving multiple design objectives at the same time. Unlike most methods, no a priori knowledge of an upper bound for velocity magnitude is used. An adaptive version of the observer is also presented to handle a class of structured uncertainties in manipulator model. Simulation example illustrates low noise sensitivity of the globally convergent observer in comparison with semi-globally convergent observers. © 2009 IEEE  

The Dual-Arm Cam-Lock (DACL) robot manipulators are reconfigurable arms formed by two parallel cooperative manipulators. Some of their joints may lock into each other. Therefore, the arms normally operate redundantly. However, when higher structural stiffness is needed these two arms can lock into each other in specific joints and loose some degrees of freedom. In this paper, the dynamics of the DACL robot is discussed and parametrically formulated. On the other hand, the criteria and implementation of genetic algorithm (GA) to optimize the configuration of DACL robot manipulators at a specific point with the objective to maximize the cooperatively applicable task-space force in a desired... 

Cooperative systems have been extensively investigated in literature. Herein the criteria and implementation for finding the optimal configuration of the Dual-Arm Cam-Lock (DACL) robot manipulators at a specific point with the objective to optimize the applicable task-space force in a desired direction are addressed. The DACL robot manipulators are reconfigurable arms formed by two parallel cooperative manipulators. Some of their joints may lock into each other. Therefore, the arms normally operate redundantly. However, when higher structural stiffness is needed these two arms can lock into each other in specific joints and loose some degrees of freedom. The dynamics of the DACL robot is... 

In this paper, a new fuzzy coordination method based on Interaction Prediction Principle (IPP) is presented for the optimal control of robot manipulators. For this purpose, the robot manipulator is considered as a two-level large-scale system where in the first level, the overall system is decomposed into several subsystems. Each subsystem can include one or more consecutive links and joints. In the second level, a fuzzy interaction prediction system is introduced for coordination of the overall system where a critic vector is also used for evaluation of its performance. The simulation results of using the proposed novel approach ,for optimal control of robot manipulators, show its... 

This paper proposes a method to suboptimally tune the control parameters in a conventional Lyapunov-Based method which shares the same concept of control design with sliding mode approach as applied to the robot manipulators. Optimal tuning of such parameters involves handling of nonlinearities in system dynamics and cost functions, which makes the problem challenging. We propose a step-by-step numerical algorithm that select suboptimal parameters while ensuring system stability. The controller is, suboptimal due to the facts that (1) it is in the form of a Slotine-type sliding mode control, (2) the numerical recursive algorithm might fall into a local minimum, and (3) the controller...