Showing papers in "Journal of Intelligent and Robotic Systems in 2008"
TL;DR: The outline to mapless navigation includes reactive techniques based on qualitative characteristics extraction, appearance-based localization, optical flow, features tracking, plane ground detection/tracking, etc... the recent concept of visual sonar has also been revised.
Abstract: Mobile robot vision-based navigation has been the source of countless research contributions, from the domains of both vision and control. Vision is becoming more and more common in applications such as localization, automatic map construction, autonomous navigation, path following, inspection, monitoring or risky situation detection. This survey presents those pieces of work, from the nineties until nowadays, which constitute a wide progress in visual navigation techniques for land, aerial and autonomous underwater vehicles. The paper deals with two major approaches: map-based navigation and mapless navigation. Map-based navigation has been in turn subdivided in metric map-based navigation and topological map-based navigation. Our outline to mapless navigation includes reactive techniques based on qualitative characteristics extraction, appearance-based localization, optical flow, features tracking, plane ground detection/tracking, etc... The recent concept of visual sonar has also been revised.
649 citations
TL;DR: A system is presented that tracks pedestrians across a scene of interest and recognizes a set of human activities and a framework is developed for the placement of multiple cameras to observe a scene.
Abstract: With the proliferation of security cameras, the approach taken to monitoring and placement of these cameras is critical This paper presents original work in the area of multiple camera human activity monitoring First, a system is presented that tracks pedestrians across a scene of interest and recognizes a set of human activities Next, a framework is developed for the placement of multiple cameras to observe a scene This framework was originally used in a limited X, Y, pan formulation but is extended to include height (Z) and tilt Finally, an active dual-camera system for task recognition at multiple resolutions is developed and tested All of these systems are tested under real-world conditions, and are shown to produce usable results
97 citations
TL;DR: The higher performance of the type-2 FLC in compensating for larger magnitudes of uncertainties with severe nonlinearities is shown through a set of numerical experiments and by comparing it against its type-1 counterpart.
Abstract: A type-2 fuzzy logic controller (FLC) is proposed in this article for robot manipulators with joint elasticity and structured and unstructured dynamical uncertainties. The proposed controller is based on a sliding mode control strategy. To enhance its real-time performance, simplified interval fuzzy sets are used. The efficiency of the control scheme is further enhanced by using computationally inexpensive input signals independently of the noisy torque and acceleration signals, and by adopting a trade off strategy between the manipulator's position and the actuators' internal stability. The controller is validated through a set of numerical experiments and by comparing it against its type-1 counterpart. It is shown through these experiments the higher performance of the type-2 FLC in compensating for larger magnitudes of uncertainties with severe nonlinearities.
88 citations
TL;DR: A brief overview of current airworthiness certification procedures and requirements for manned aviation is presented, followed by a survey of the current status of Unmanned Aircraft System (UAS) regulations in the US but also internationally.
Abstract: An aircraft (manned aircraft) may enter safely and legally into the US National Airspace System if and only if it has an airworthiness certificate complying with Federal Aviation Administration requirements. Although corresponding requirements, procedures and regulations for unmanned aircraft are in early development stages, they are expected to be similar to those set for manned aviation. This paper presents a brief overview of current airworthiness certification procedures and requirements for manned aviation, followed by a survey of the current status of Unmanned Aircraft System (UAS) regulations in the US but also internationally. Future perspectives of UAS regulation are discussed along with a proposed UAS classification for certification purposes, presentation of a possible certification roadmap, as well as regulatory paths for ultra-light UAS.
68 citations
TL;DR: This paper presents a new SLAM method which uses vertical lines extracted from an omni-directional camera image and horizontal lines from the range sensor data which reduces the effect of illumination and partial occlusion.
Abstract: An autonomous mobile robot must have the ability to navigate in an unknown environment. The simultaneous localization and map building (SLAM) problem have relation to this autonomous ability. Vision sensors are attractive equipment for an autonomous mobile robot because they are information-rich and rarely have restrictions on various applications. However, many vision based SLAM methods using a general pin-hole camera suffer from variation in illumination and occlusion, because they mostly extract corner points for the feature map. Moreover, due to the narrow field of view of the pin-hole camera, they are not adequate for a high speed camera motion. To solve these problems, this paper presents a new SLAM method which uses vertical lines extracted from an omni-directional camera image and horizontal lines from the range sensor data. Due to the large field of view of the omni-directional camera, features remain in the image for enough time to estimate the pose of the robot and the features more accurately. Furthermore, since the proposed SLAM does not use corner points but the lines as the features, it reduces the effect of illumination and partial occlusion. Moreover, we use not only the lines at corners of wall but also many other vertical lines at doors, columns and the information panels on the wall which cannot be extracted by a range sensor. Finally, since we use the horizontal lines to estimate the positions of the vertical line features, we do not require any camera calibration. Experimental work based on MORIS, our mobile robot test bed, moving at a human's pace in the real indoor environment verifies the efficacy of this approach.
59 citations
TL;DR: With the platform’s kinematic model and the motors’ dynamic model associated two unknown parameters, the adaptive robust controller is synthesized via the integral backstepping approach.
Abstract: This paper presents an adaptive robust control method for trajectory tracking and path following of an omni-directional wheeled mobile platform with actuators' uncertainties. The polar-space kinematic model of the platform with three independent driving omnidirectional wheels equally spaced at 120 from one another is briefly introduced, and the dynamic models of the three uncertain servomotors mounted on the driving wheels are also described. With the platform's kinematic model and the motors' dynamic model associated two unknown parameters, the adaptive robust controller is synthesized via the integral backstepping approach. Computer simulations and experimental results are conducted to show the effectiveness and merits of the proposed control method in comparison with a conventional PI feedback control method.
43 citations
TL;DR: A comprehensive user-friendly general-purpose software package has been developed using VC++ to obtain the optimal solutions of any complex problem using DE algorithm.
Abstract: A general method for computing minimum cost trajectory planning for industrial robot manipulators is presented. The aim is minimization of a cost function with constraints namely joint positions, velocities, jerks and torques by considering dynamic equations of motion. A clamped cubic spline curve is used to represent the trajectory. This is a non-linear constrained optimization problem with five objective functions, 30 constraints and 144 variables. The cost function is a weighted balance of transfer time, mean average of actuators efforts and power, singularity avoidance, joint jerks and joint accelerations. The problem is solved by two evolutionary techniques such as Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Differential Evolution (DE). Numerical applications for a six link robotic manipulator --- STANFORD robot (pick and place operation) and a two link planar manipulator (motion in the presence of obstacles) are illustrated. The results obtained from the Proposed techniques (NSGA-II and DE) are compared for different values of weighting coefficients. The influences of the algorithm parameters and weight factors on algorithm performance are analyzed. The DE algorithm converges quickly than NSGA-II. Also DE algorithm gives better results than NSGA-II in majority of cases. A comprehensive user-friendly general-purpose software package has been developed using VC++ to obtain the optimal solutions of any complex problem using DE algorithm.
42 citations
TL;DR: An autonomous path planning method for target capturing in Cartesian space that can drive the manipulator to approach the target along the closest path and avoid the dynamic singularities, and the experiment results validate the proposed algorithm.
Abstract: Space robotic systems are expected to play an increasingly important role in the future. The robotic on-orbital service, whose key is the capturing technology, becomes research hot in recent years. In this paper, the authors propose an autonomous path planning method for target capturing. The task is described in Cartesian space and it can drive the manipulator to approach the target along the closest path. Firstly, the target feature is extracted based on the measured information via the hand-eye camera, and the target pose (position and orientation) and velocities (linear velocity and angular velocity) are estimated using Kalman filtering technology. Then, a numerically feasible approach is presented to plan the manipulator motion and avoid the dynamic singularities, which are transformed into real-time kinematic singularities avoiding problem. Thirdly, the potential disturbance on the base due to the manipulator's motion is estimated, and the joint rates are autonomously adjusted to reduce the disturbance if it is beyond the allowed bound. At last, a ground experiment system is set up based on the concept of dynamic emulation and kinematic equivalence. With the experiment system, the autonomous target capturing experiments are conducted. The experiment results validate the proposed algorithm.
42 citations
TL;DR: Simulation results show good performance of the proposed method in motion tracking as well force tracking in presence of model mismatches and time delay uncertainties.
Abstract: In this paper, a simple structure design with arbitrary motion/force scaling to control teleoperation systems, with model mismatches is presented. The goal of this paper is to achieve transparency in presence of uncertainties. The master---slave systems are approximated by linear dynamic models with perturbed parameters, which is called the model mismatch. Moreover, the time delay in communication channel with uncertainties is considered. The stability analysis will be considered for two cases: (1) stability under time delay uncertainties and (2) stability under model mismatches. For the first case, two local controllers are designed. The first controller is responsible for tracking the master commands, while the second controller is in charge of force tracking as well as guaranteeing stability of the overall closed-loop system. In the second case, an additional term will be added to the control law to provide robustness to the closed-loop system. Moreover, in this case, the local slave controller guarantees the position tracking and the local master controller guarantees stability of the inner closed-loop system. The advantages of the proposed method are two folds: (1) robust stability of the system against model mismatches is guaranteed and (2) structured system uncertainties are well compensated by applying independent controllers to the master and the slave sites. Simulation results show good performance of the proposed method in motion tracking as well force tracking in presence of model mismatches and time delay uncertainties.
39 citations
TL;DR: An all-around sensing system based on an integrated ADAS that senses all directions using 2 cameras and 8 sonars, recognizes the driving environment via lane and vehicle detection, and construct a novel bird’s-eye view HMI of the environment for easy comprehension that even gives a proper warning signal in case of imminent danger is presented.
Abstract: Advanced driver assistance systems (ADAS) support the driver's decision making to increase safety and comfort by providing an ergonomic display of the driving environment as well as issuing the warning signals or even exerting active control in case of dangerous conditions. Most previous research and products intend to offer only a single warning service, such as lane departure warning, collision warning, lane change assistance, etc. Although each component of these functions elevates the driving safety and convenience to a certain degree, a new type of ADAS will be developed to integrate all of the important functions with an efficient human---machine interface (HMI) framework for various driving conditions. We present an all-around sensing system based on an integrated ADAS that senses all directions using 2 cameras and 8 sonars, recognizes the driving environment via lane and vehicle detection, and construct a novel bird's-eye view HMI of the environment for easy comprehension that even gives a proper warning signal in case of imminent danger. It was tested on our experimental vehicle with a good demonstration its working. Further, it has a good potential for commercial use by virtue of the low cost of the sensors used.
37 citations
TL;DR: Experimental results with a four-degree-of-freedom flexible-joint manipulator under constrained-motion task, demonstrate that the controller architecture can enhance the robot impedance performance effectively.
Abstract: Some practical issues associated with enhancing the Cartesian impedance performance of flexible joint manipulator are investigated. A digital signal processing/field programmable gate array (DSP/FPGA) structure is proposed to realize the singular perturbation based impedance controller. To increase the bandwidth of torque control and minimize the joint torque ripple, boundary layer system and field-oriented control (FOC) are fully implemented in a FPGA of each joint. The kernel of the hardware system is a peripheral component interface (PCI)-based high speed floating-point DSP for the Cartesian level control, and FPGA for high speed (200 us cycle time) multipoint low-voltage differential signaling (M-LVDS) serial data bus communication between robot Cartesian level and joint level. Experimental results with a four-degree-of-freedom flexible-joint manipulator under constrained-motion task, demonstrate that the controller architecture can enhance the robot impedance performance effectively.
TL;DR: A method for estimating the vehicle global position in a network of roads by means of visual odometry, where the ego-motion of the vehicle relative to the road is computed using a stereo-vision system mounted next to the rear view mirror of the car.
Abstract: This paper describes a method for estimating the vehicle global position in a network of roads by means of visual odometry. To do so, the ego-motion of the vehicle relative to the road is computed using a stereo-vision system mounted next to the rear view mirror of the car. Feature points are matched between pairs of frames and linked into 3D trajectories. Vehicle motion is estimated using the non-linear, photogrametric approach based on RANSAC. This iterative technique enables the formulation of a robust method that can ignore large numbers of outliers as encountered in real traffic scenes. The resulting method is defined as visual odometry and can be used in conjunction with other sensors, such as GPS, to produce accurate estimates of the vehicle global position. The obvious application of the method is to provide on-board driver assistance in navigation tasks, or to provide a means for autonomously navigating a vehicle. The method has been tested in real traffic conditions without using prior knowledge about the scene nor the vehicle motion. We provide examples of estimated vehicle trajectories using the proposed method and discuss the key issues for further improvement.
TL;DR: An efficient localization algorithm based on a vector-matching technique for mobile robots with laser range finders using a map with line-segment vectors that enables efficient vector extraction from scanned data is described.
Abstract: This paper describes an efficient localization algorithm based on a vector-matching technique for mobile robots with laser range finders As a reference the method uses a map with line-segment vectors, which can be built from a CAD layout of the indoor environment The contribution of this work lies in the overall localization process First, the proposed sequential segmentation method enables efficient vector extraction from scanned data Second, a reliable and efficient vector-matching technique is proposed Finally, a cost function suitable for vector-matching is proposed for nonlinear pose estimation with solutions for both nonsingular and singular cases Simulation results show that the proposed localization method works reliably even in a noisy environment The algorithm was implemented for our wheelchair-based mobile robot and evaluated in a 135 m long corridor environment
TL;DR: Methods that only use local sensor information to identify search targets require fewer message exchanges and create less interference between robots than existing shared approaches, and search progress and completion are more consistent due to the reduction in interference.
Abstract: Although explicit coordination of team search may provide solid performance for small team sizes, it has been shown that such methods do not scale to larger teams due to limited communications bandwidth and computational requirements. In addition, methods that rely upon persistent, reliable network connections may have limited applicability to real-world search problems. In this work, we explore implicit cooperation enabled through sharing of search progress information. Prior research shows cooperation paradigms in which team members share a global task list result in interference and duplication of search when members choose the same search areas. Methods that only use local sensor information to identify search targets require fewer message exchanges and create less interference between robots than existing shared approaches. In addition, search progress and completion are more consistent due to the reduction in interference. Results based on simulations and physical experiments are presented that compare performance in terms of time-to-cover, consistency, and interference.
TL;DR: A fuzzy logic control concept has been applied in order to control the end-effector position, velocity and acceleration and it turns out to be convenient in simulation, allied with inner-loop classical control.
Abstract: This paper introduces a cable-suspended robot, the vehicle simulation system, designed for pilot and driver training. The main idea of this work is to make a system that will provide realistic simulations of vehicle motion using virtual reality and a motion platform. A method to produce inertial forces acting on the vehicle user is proposed. A detailed description of the robot's dynamics constraints is provided, accompanied with a numerical solution. Using the developed mathematical model, the robot workspace is analyzed, as well as the influence of the end-effector orientation angle ranges on the available workspace. Adequate robot platform motion is provided through four control systems in a form of a cascade control with a fuzzy logic controller in outer loops. The cable robot is non-linear and difficult from a classical control point of view, since it requires a local linearization of the dynamics equations. A fuzzy logic control concept has been applied in order to control the end-effector position, velocity and acceleration and it turns out to be convenient in simulation, allied with inner-loop classical control. As the system is under-constrained, with nine unknown cable tensions and six dynamics equations, an optimization method is used. The control complexity is increased by the requirement, specific to cable robots, of maintaining positive cable tensions. The system simulations are done using a virtual reality environment and results are presented accompanied with the discussion.
TL;DR: This paper presents a class of OFT controllers for torque-constrained robots, and presents a detailed experimental study of six control schemes, which were tested in a two degrees-of-freedom direct-drive robot, confirming the advantages of the proposed methodology.
Abstract: The trajectory tracking of robot manipulators is addressed in this paper. Two important practical situations are considered: the fact that robot actuators have limited power, and that only position measurements are carried out. Let us notice that a few solutions for the torque-bounded OFT (output feedback tracking) control has been proposed. In this paper we contribute to this subject by presenting a class of OFT controllers for torque-constrained robots. The theory of singularly perturbed systems is crucial in the analysis of the closed-loop system trajectories. As a second contribution of this paper, we present a detailed experimental study of six control schemes, which were tested in a two degrees-of-freedom direct-drive robot, confirming the advantages of the proposed methodology.
TL;DR: A novel waypoint-based robot navigation method that combines reactive and deliberative actions, which uses reactive exploration to generate waypoints that can be used by a deliberative system to plan future movements through the same environment.
Abstract: In this paper we propose a novel waypoint-based robot navigation method that combines reactive and deliberative actions. The approach uses reactive exploration to generate waypoints that can then be used by a deliberative system to plan future movements through the same environment. The waypoints are used largely to provide the interface between reactive and deliberative navigation and a range of methods could be used for either type of navigation. In the current work, an incremental decision tree method is used to navigate the robot reactively from the specified initial position to its destination avoiding obstacles in its path and a genetic algorithm method is used to perform the deliberative navigation. The new method is shown to have a number of practical advantages. Firstly, in contrast with many deliberative approaches, complete knowledge of the environment is not required, nor is it necessary to make assumptions regarding the geometry of obstacles. Secondly, the presence of a reactive navigator means it is always possible to continue directed movements in unknown or changing environments or when time constraints become particularly demanding. Thirdly, the use of waypoints allows escape from certain obstacle configurations that would normally trap robots navigated under the control of purely reactive methods. In addition, the results presented in this paper from a number of realistic simulated environments show that the adoption of waypoints significantly reduces the time to calculate a deliberative path.
TL;DR: This work explores the effect of control strategies of varying complexity and environmental factors on the performance of a team of robots at a foraging task when using physical robots (the Minnesota Distributed Autonomous Robotic Team).
Abstract: Swarm techniques, where many simple robots are used instead of complex ones for performing a task, promise to reduce the cost of developing robot teams for many application domains. The challenge lies in selecting an appropriate control strategy for the individual units. This work explores the effect of control strategies of varying complexity and environmental factors on the performance of a team of robots at a foraging task when using physical robots (the Minnesota Distributed Autonomous Robotic Team). Specifically we study the effect of localization and of simple indirect communication techniques on task completion time using two sets of foraging experiments. We also present results for task performance with varying team sizes and target distributions. As indicated by the results, control strategies with increasing complexity reduce the variance in the performance, but do not always reduce the time to complete the task.
TL;DR: A necessary and sufficient graphical condition is proposed to guarantee that the headings of all robots converge to the same heading and it is shown that the globally reachable node having no neighbors serves as a group leader as a special case.
Abstract: Coordinated collective motion of groups of autonomous mobile robots is studied. A qualitative analysis for the collective dynamics of multiple autonomous robots with directed interconnected topology using nearest neighbor rules is given. A necessary and sufficient graphical condition is proposed to guarantee that the headings of all robots converge to the same heading. The graph having a globally reachable node plays a crucial role in convergence analysis. Furthermore, we show that the globally reachable node having no neighbors serves as a group leader as a special case
TL;DR: A method to obtain a plan that interleaves a sampling-based exploration of ${\mathcal C}$-space with an efficient computation of harmonic functions is proposed and implemented in a planner.
Abstract: Haptic devices allow a user to feel either reaction forces from virtual interactions or reaction forces reflected from a remote site during a bilateral teleoperation task. Also, guiding forces can be exerted to train the user in the performance of a virtual task or to assist him/her to safely teleoperate a robot. The generation of guiding forces relies on the existence of a motion plan that provides the direction to be followed to reach the goal from any free configuration of the configuration space ( ${\mathcal C}$ -space). This paper proposes a method to obtain such a plan that interleaves a sampling-based exploration of ${\mathcal C}$ -space with an efficient computation of harmonic functions. A deterministic sampling sequence (with a bias based on harmonic function values) is used to obtain a hierarchical cell decomposition model of ${\mathcal C}$ -space. A harmonic function is iteratively computed over the partially known model using a novel approach. The harmonic function is the navigation function used as motion plan. The approach has been implemented in a planner (called the Kautham planner) that, given an initial and a goal configuration, provides: (a) a channel of cells connecting the cell that contains the initial configuration with the cell that contains the goal configuration; (b) two harmonic functions over the whole ${\mathcal C}$ -space, one that guides motions towards the channel and another that guides motions within the channel towards the goal; and (c) a path computed over a roadmap built with the free samples of the channel. The harmonic functions and the solution path are then used to generate the guiding forces for the haptic device. The planning approach is illustrated with examples on 2D and 3D workspaces.
TL;DR: A new notion of joint, defined in terms of the state of motor and type of the elastic or rigid element, gear and/or link that follows after the motor, is introduced and special attention is paid to the motion of the flexible links in the robotic configuration.
Abstract: A new notion of joint, defined in terms of the state of motor (active or locked) and type of the elastic or rigid element, gear and/or link that follows after the motor, is introduced. Special attention is paid to the motion of the flexible links in the robotic configuration. The paper deals with the relationship between the equation of elastic line equilibrium, the "Euler---Bernoulli approach" (EBA), and equation of motion at the point of elastic line tip, the "Lumped-mass approach" (LMA). The Euler---Bernoulli equations (which have for a long time been used in the literature) should be expanded according to the requirements of the motion complexity of elastic robotic systems. The Euler---Bernoulli equation (based on the known laws of dynamics) should be supplemented with all the forces that are participating in the formation of the elasticity moment of the considered mode. This yields the difference in the structure of Euler---Bernoulli equations for each mode. The stiffness matrix is a full matrix. Mathematical model of the actuators also comprises coupling between elasticity forces. Particular integral of Daniel Bernoulli should be supplemented with the stationary character of elastic deformation of any point of the considered mode, caused by the present forces. General form of the elastic line is a direct outcome of the system motion dynamics, and cannot be described by one scalar equation but by three equations for position and three equations for orientation of every point on that elastic line. The choice of reference trajectory is analyzed. Simulation results are shown for a selected robotic example involving the simultaneous presence of elasticity of the gear and of the link (two modes), as well as the environment force dynamics.
TL;DR: A robust regression model is proposed for segment extraction in static and dynamic environments using the MM-estimate to consider the noise of sensor data and the outliers that correspond to dynamic objects such as the people in motion.
Abstract: Segment-based maps as sub-class of feature-based mapping have been widely applied in simultaneous localization and map building (SLAM) in autonomous mobile robots. In this paper, a robust regression model is proposed for segment extraction in static and dynamic environments. We adopt the MM-estimate to consider the noise of sensor data and the outliers that correspond to dynamic objects such as the people in motion. MM-estimates are interesting as they combine high efficiency and high breakdown point in a simple and intuitive way. Under the usual regularity conditions, including symmetric distribution of the errors, these estimates are strongly consistent and asymptotically normal. This robust regression technique is integrated with the extended Kalman filter (EKF) to build a consistent and globally accurate map. The EKF is used to estimate the pose of the robot and state of the segment feature. The underpinning experimental results that have been carried out in static and dynamic environments illustrate the performance of the proposed segment extraction method.
TL;DR: In this article, a hybrid integrated dynamic control algorithm for humanoid locomotion mechanism is presented, which involves two feedback loops: model-based dynamic controller including impart-force controller and reinforcement learning feedback controller around zero-moment point.
Abstract: In this paper, hybrid integrated dynamic control algorithm for humanoid locomotion mechanism is presented The proposed structure of controller involves two feedback loops: model-based dynamic controller including impart-force controller and reinforcement learning feedback controller around zero-moment point The proposed new reinforcement learning algorithm is based on modified version of actor-critic architecture for dynamic reactive compensation Simulation experiments were carried out in order to validate the proposed control approachThe obtained simulation results served as the basis for a critical evaluation of the controller performance
TL;DR: In the proposed approach, the partitioning is performed offline and a probabilistic neural network is trained by the set of points at the borders of the state-space partitions, used as a system-state-based control-law classifier and the online computational effort is minimized.
Abstract: This paper proposes an approach for reducing the computational complexity of a model-predictive-control strategy for discrete-time hybrid systems with discrete inputs only. Existing solutions are based on dynamic programming and multi-parametric programming approaches, while the one proposed in this paper is based on a modified version of performance-driven reachability analyses. The algorithm abstracts the behaviour of the hybrid system by building a 'tree of evolution'. The nodes of the tree represent the reachable states of a process, and the branches correspond to input combinations leading to designated states. A cost-function value is associated with each node and based on this value the exploration of the tree is driven. For any initial state, an input sequence is thus obtained, driving the system optimally over a finite horizon. According to the model predictive strategy, only the first input is actually applied to the system. The number of possible discrete input combinations is finite and the feasible set of the states of the system may be partitioned according to the optimization results. In the proposed approach, the partitioning is performed offline and a probabilistic neural network (PNN) is then trained by the set of points at the borders of the state-space partitions. The trained PNN is used as a system-state-based control-law classifier. Thus, the online computational effort is minimized and the control can be implemented in real time.
TL;DR: A biomechanical model of the index finger of the human hand is developed based on the human anatomy with fuzzy sliding mode control and an unexpected joint friction is induced on the prosthetic finger on its way.
Abstract: In order to improve the life quality of amputees, providing approximate manipulation ability of a human hand to that of a prosthetic hand is considered by many researchers. In this study, a biomechanical model of the index finger of the human hand is developed based on the human anatomy. Since the activation of finger bones are carried out by tendons, a tendon configuration of the index finger is introduced and used in the model to imitate the human hand characteristics and functionality. Then, fuzzy sliding mode control where the slope of the sliding surface is tuned by a fuzzy logic unit is proposed and applied to have the finger model to follow a certain trajectory. The trajectory of the finger model, which mimics the motion characteristics of the human hand, is pre-determined from the camera images of a real hand during closing and opening motion. Also, in order to check the robust behaviour of the controller, an unexpected joint friction is induced on the prosthetic finger on its way. Finally, the resultant prosthetic finger motion and the tendon forces produced are given and results are discussed.
TL;DR: A story of interaction among characters with different social positioning, such that reasoning on the body of one of them is central is analyzed, by resorting to episodic formulae, a method of representation developed by the present author and often applied during the last several years.
Abstract: This article develops two threads. The first thread argues that the narrative dimension of social interaction is important to societies of embodied agents: not only to animated avatars in virtual environments (for which, behaviour specification languages are useful, simplifying the distinct task of feeding a narrative into the system), but also, arguably, in societies of robots, because categories of patterns of action can arguably be usefully captured by modifications of levels of abstraction originally developed by structuralism for folktale studies. This first thread does not depend, for its validity, on the second thread. The other thread of this paper is to analyze a story of interaction among characters with different social positioning, such that reasoning on the body of one of them is central. We develop the analysis by resorting to episodic formulae, a method of representation developed by the present author and often applied during the last several years.
TL;DR: A biologically inspired multi-level neural-schema architecture for prey catching and predator avoidance in single and multiple autonomous robotic systems inspired on anuran (frogs and toads) neuroethological studies and wolf pack group behaviors is presented.
Abstract: The paper presents a biologically inspired multi-level neural-schema architecture for prey catching and predator avoidance in single and multiple autonomous robotic systems The architecture is inspired on anuran (frogs and toads) neuroethological studies and wolf pack group behaviors The single robot architecture exploits visuomotor coordination models developed to explain anuran behavior in the presence of preys and predators The multiple robot architecture extends the individual prey catching and predator avoidance model to experiment with group behavior The robotic modeling architecture distinguishes between higher-level schemas representing behavior and lower-level neural structures representing brain regions We present results from single and multiple robot experiments developed using the NSL/ASL/MIRO system and Sony AIBO ERS-210 robots
TL;DR: This work studies the dynamic modeling method for a service robot with Omni-directional Mobile ManipulatorS configuration with left invariant representation, and presents a legible and canonical dynamic model representing the relation between the inputs and the generalized dynamic load wrenches.
Abstract: This work studies the dynamic modeling method for a service robot with Omni-directional Mobile ManipulatorS configuration. Based on screw theory, Lie group notations, reciprocal product of twist and wrench, and Jourdain principle, the robot's motion equations including the whole body manipulation are formulated with left invariant representation. A legible and canonical dynamic model representing the relation between the inputs and the generalized dynamic load wrenches is presented. Considering the tradeoff between the symbolic concision, the modularization in code realization and the computation load, the dynamic model is decomposed into succinct block factorizations, and the basic computation unites are boiled down to the adjoint map corresponding to each joint. The traditional Lie bracket operation is extended to a generalized form. Computation efficiency, for the coefficient matrixes of the system motion equation, is discussed based on its special representation form. The generalization of the modeling method with Lie group and algebra tool is also summarized.
TL;DR: A trajectory tracking control system for hydraulically actuated robotic mechanism that diminishes the flattery delay in the output response and exhibits a very accurate foot trajectory tracking with very small tracking error with the proposed controller.
Abstract: Hydraulically actuated robotic mechanisms are becoming popular for field robotic applications for their compact design and large output power. However, they exhibit nonlinearity, parameter variation and flattery delay in the response. This flattery delay, which often causes poor trajectory tracking performance of the robot, is possibly caused by the dead zone of the proportional electromagnetic control valves and the delay associated with oil flow. In this investigation, we have proposed a trajectory tracking control system for hydraulically actuated robotic mechanism that diminishes the flattery delay in the output response. The proposed controller consists of a robust adaptive fuzzy controller with self-tuned adaptation gain in the feedback loop to cope with the parameter variation and disturbances and a one-step-ahead fuzzy controller in the feed-forward loop for hydraulic dead zone pre-compensation. The adaptation law of the feedback controller has been designed by Lyapunov synthesis method and its adaptation rate is varied by fuzzy self-tuning. The variable adaptation rate helps to improve the tracking performance without sacrificing the stability. The proposed control technique has been applied for locomotion control of a hydraulically actuated hexapod robot under independent joint control framework. For tracking performance of the proposed controller has also been compared with classical PID controller, LQG state feedback controller and static fuzzy controller. The experimental results exhibit a very accurate foot trajectory tracking with very small tracking error with the proposed controller.
TL;DR: The simulation results demonstrate that the PRBPS realizes PR with very good robustness to the parameter uncertainties, and the control input torques and settling time are reduce greatly in the case of large initial feature errors.
Abstract: The position regulation problem of an eye-in-hand type of parallel robot based pointing systems (PRBPS) is considered in this paper. A fuzzy logic system is first designed to compensate for the uncertainties of the parallel robot and the uncertainty of the image Jacobian, then a hybrid controller (HC) including the image-based nonlinear controller and the adaptive supervisory fuzzy logic controller (ASFLC) is derived by using the Lyapunov direct method to realize the position regulation (PR). The stability of the closed-loop system in the Lyapunov sense is proven theoretically. The fuzzy scaling matrix is combined with the HC to improve the performance of the control system. The simulation results demonstrate that the PRBPS realizes PR with very good robustness to the parameter uncertainties, and the control input torques and settling time are reduce greatly in the case of large initial feature errors.