International Journal of Advanced Robotic Systems
Volume 3 Number 4 December 2006 |
Logic-dynamic approach to fault diagnosis in mechatronic systems, Page 285-294 Abstract:This paper presents a problem of fault detection and isolation (FDI) in mechatronic systems described by nonlinear dynamic models with such types of no differentiable nonlinearities as saturation, Coulomb friction, backlash, and hysteresis. To solve this problem, so-called logic-dynamic approach is suggested. This approach consists of three main steps: replacing the initial nonlinear system by certain linear logic-dynamic system, obtaining the bank of linear logic-dynamic observers, and transforming these observes into the nonlinear ones. Logic-dynamic approach allows one to use the linear FDI methods for diagnosis in nonlinear mechatronic systems.
Comparison of Localization Methods for a Robot Soccer Team, Page 295-302 Abstract:In this work, several localization algorithms that are designed and implemented for Cerberus'05 Robot Soccer Team are analyzed and compared. These algorithms are used for global localization of autonomous mobile agents in the robotic soccer domain, to overcome the uncertainty in the sensors, environment and the motion model. The algorithms are Reverse Monte Carlo Localization (R-MCL), Simple Localization (S-Loc) and Sensor Resetting Localization (SRL). R-MCL is a hybrid method based on both Markov Localization (ML) and Monte Carlo Localization (MCL) where the ML module finds the region where the robot should be and MCL predicts the geometrical location with high precision by selecting samples in this region. S-Loc is another localization method where just one sample per percept is drawn, for global localization. Within this method another novel method My Environment (ME) is designed to hold the history and overcome the lack of information due to the drastically decrease in the number of samples in S-Loc. ME together with S-Loc is used in the Technical Challenges in Robocup 2005 and play an important role in ranking the First Place in the Challenges. In this work, these methods together with SRL, which is a widely used successful localization algorithm, are tested with both offline and real-time tests. First they are tested on a challenging data set that is used by many researches and compared in terms of error rate against different levels of noise, and sparsity. Besides time required recovering from kidnapping and speed of the methods are tested and compared. Then their performances are tested with real-time tests with scenarios like the ones in the Technical Challenges in ROBOCUP. The main aim is to find the best method which is very robust and fast and requires less computational power and memory compared to similar approaches and is accurate enough for high level decision making which is vital for robot soccer.
Natural Heat-Sinking Control Method for High-Speed Actuation of the SMA, Page 303-312 Abstract: This paper describes two methodologies for increasing the actuation speed of the shape memory alloy (SMA) actuator in ambient environment. The first method involves the implementation of a simple, light-weight heat sink, which consists only of a combination of an outer metal tube with the silicone grease, but able to cool the heated alloy effectively. The second method describes a high current pulse actuation that actuates the alloy fastly using pulses in the milliseconds order. We hypothesize that a fast actuation of the SMA results in small increase in temperature, due to energy transformation from heat energy to the kinetic energy in the SMA. This new heating method revolutionizes the actuation of the alloy for a significantly faster response.
Sociable Robots through Self-maintained Energy, Page 313-322 Abstract: Research of autonomous mobile robots has mostly emphasized interaction and coordination that are natually inspired from biological behavior of birds, insects, and fish: flocking, foraging, collecting, and sharing. However, most research has been only focused on autonomous behaviors in order to perform robots like animals, whereas it is lacked of determinant to those behaviours: energy. Approaching to clusted amimal and the higher, collective and sharing food among individuals are major activity to keep society being. This paper issues an approach to sociable robots using self-maintained energy in cooperative mobile robots, which is dominantly inspired from swarm behavior of collecting and sharing food of honey-bee and ant. Autonomous mobile robots are usually equipped with a finite energy, thus they can operate in a finite time. To overcome the finitude, we describe practical deployment of mobile robots that are capable of carrying and exchanging fuel to other robots. Mechanism implementation including modular hardware and control architecture to demonstrate the capabicities of the approach is presented. Subsequently, the battery exchange algorithm basically based on probabilistic modeling of total energy on each robot located in its local vicinity is described. The paper is concluded with challenging works of chain of mobile robots, rescue, repair, and relation of heterogeneous robots.
Online Self-Tuning Precompensation for a PID Heading Control of a Flying Robot, Page 323-330 Abstract: In this paper, an online self-tuning precompensation for a Proportional-Integral-Derivative (PID) controller is proposed to control heading direction of a flying robot. The flying robot is a highly nonlinear plant, it is a modified X-Cell 60 radio-controlled helicopter. Heading direction is controlled to evaluate efficiency of the proposed precompensation algorithm. The heading control is based on the conventional PID control combined with an online self-tuning precompensation so that both the desired transient and steady state responses can be achieved. The precompensation is applied to compensate unsatisfied performances of the conventional PID controller by adjusting reference command. The precompensator is based on Takagi-Sugeno’s type fuzzy model, which learns to tune itself online. The main contribution of the proposed controller is to enhance the controlled performance of the conventional PID controller by adding a self-tuning precompensator on the existing conventional PID controller. The results show that the conventional PID controller with an online self-tuning precompensation has a superior performance than the conventional PID controller. In addition, the online selftuning precompensation algorithm is implemented simply by adding the precompensator to the existing conventional PID controller and letting the self-tuning mechanism tune itself online.
Kalman Based Finite State Controller for Partially Observable Domains, Page 331-342 Abstract: A real world environment is often partially observable by the agents either because of noisy sensors or incomplete perception. Moreover, it has continuous state space in nature, and agents must decide on an action for each point in internal continuous belief space. Consequently, it is convenient to model this type of decisionmaking problems as Partially Observable Markov Decision Processes (POMDPs) with continuous observation and state space. Most of the POMDP methods whether approximate or exact assume that the underlying world dynamics or POMDP parameters such as transition and observation probabilities are known. However, for many real world environments it is very difficult if not impossible to obtain such information. We assume that only the internal dynamics of the agent, such as the actuator noise, interpretation of the sensor suite, are known. Using these internal dynamics, our algorithm, namely Kalman Based Finite State Controller (KBFSC), constructs an internal world model over the continuous belief space, represented by a finite state automaton. Constructed automaton nodes are points of the continuous belief space sharing a common best action and a common uncertainty level. KBFSC deals with continuous Gaussian-based POMDPs. It makes use of Kalman Filter for belief state estimation, which also is an efficient method to prune unvisited segments of the belief space and can foresee the reachable belief points approximately calculating the horizon N policy. KBFSC does not use an "explore and update" approach in the value calculation as TD-learning. Therefore KBFSC does not have an extensive exploration-exploitation phase. Using the MDP case reward and the internal dynamics of the agent, KBFSC can automatically construct the finite state automaton (FSA) representing the approximate optimal policy without the need for discretization of the state and observation space. Moreover, the policy always converges for POMDP problems.
Tolerance towards sensor faults: An application to a flexible arm manipulator, Page 343-350 Abstract: As more engineering operations become automatic, the need for robustness towards faults increases. Hence, a fault tolerant control (FTC) scheme is a valuable asset. This paper presents a robust sensor fault FTC scheme implemented on a flexible arm manipulator, which has many applications in automation. Sensor faults affect the system's performance in the closed loop when the faulty sensor readings are used to generate the control input. In this paper, the non-faulty sensors are used to reconstruct the faults on the potentially faulty sensors. The reconstruction is subtracted from the faulty sensors to form a compensated `virtual sensor' and this signal (instead of the normally used faulty sensor output) is then used to generate the control input. A design method is also presented in which the FTC scheme is made insensitive to any system uncertainties. Two fault conditions are tested; total failure and incipient faults. Then the scheme robustness is tested by implementing the flexible joint's FTC scheme on a flexible link, which has different parameters. Excellent results have been obtained for both cases (joint and link); the FTC scheme caused the system performance is almost identical to the fault-free scenario, whilst providing an indication that a fault is present, even for simultaneous faults.
Kinematic Analysis and Optimization of a New Compliant Parallel Micromanipulator, Page 351-358 Abstract:In this paper, a new three translational degrees of freedom (DOF) compliant parallel micromanipulator (CPM) is proposed, which has an excellent accuracy of parallel mechanisms with flexure hinges. The system is established by a proper selection of hardware and analyzed via the derived pseudo-rigid-body model. In view of the physical constraints imposed by both the piezoelectric actuators and flexure hinges, the CPM’s reachable workspace is determined analytically, where a maximum cylinder defined as an usable workspace can be inscribed. Moreover, the optimal design of the CPM with the consideration of the usable workspace size and global dexterity index simultaneously is carried out by utilizing the approaches of direct search method, genetic algorithm (GA), and particle swarm optimization (PSO), respectively. The simulation results show that the PSO is the best method for the optimization, and the results are valuable in the design of a new micromanipulator.
A Novel Reconfigurable Robot for Urban Search and Rescue, Page 359-366 Abstract: This paper presents a novel mobile robot for urban search and rescue based on reconfiguration. The system consists of three identical modules; actually each module is an entire robotic system that can perform distributed activities. To achieve highly adaptive locomotion capabilities, the robot’s serial and parallel mechanisms form an active joint, enabling it to change its shape in three dimensions. A docking mechanism enables adjacent modules to connect or disconnect flexibly and automatically. This mechanical structure and the control system are introduced in detail, followed by a description of the locomotion capabilities. In the end, the successful on-site tests confirm the principles described above and the robot’s ability.
Gain scheduling for hybrid force/velocity control in contour tracking task, Page 367-374 Abstract: In this paper a gain scheduling approach is proposed for the hybrid force/velocity control of an industrial manipulator employed for the contour tracking of objects of unknown shape. The methodology allows to cope with the configuration dependent dynamics of the manipulator during a constrained motion and therefore a significant improvement of the performance results. Experimental results obtained with an industrial SCARA manipulator demonstrate the effectiveness of the technique.
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ARS Web 2006 |