This paper presents a methodology for image-to-space path planning of a SCARA manipulator with a single static color camera. The method proposes a two step algorithm for estimating object position on the image plane and then mapping into space to find required angular values of the manipulator joints. Tests were carried with a computational routine to estimate position on the image plane of a set of different fruits under natural light conditions. Finally the method was tested using a robotic arm and similarly structured objects. Hardware and software implementation of the present method is of low cost when compared to current commercial technology, and operational results are promising but dependent on environmental illumination control and camera calibration accuracy. The methodology is intended to be applied in the automatic classification of fruits.

Manipulators with 3-RSR topology are three-degree-of-freedom parallel manipulators that may be either spherical or mixed-motion manipulators. The inverse position analysis (IPA) and the workspace determination of 3-RSR manipulators are addressed by means of a new approach. The new approach is centered on a particular form of the closure equations called compatibility equations. The compatibility equations contain only the six coordinates (end-effector coordinates) which locates the end-effector pose (position and orientation) with respect to the frame, and the geometric constants of the manipulator. When the manipulator geometry is assigned, the common solutions of the compatibility equations are the end-effector coordinates which identify the end-effector poses belonging to the manipulator workspace. Moreover, they can be the starting point to easily solve the IPA. The presented compatibility equations can be also used to solve the position synthesis of the 3-RSR manipulator. This way of solving the position synthesis will demonstrate that only approximated solutions exist when more than eight end-effector poses are given.

A new approach to the design of a polytopic gain scheduled H∞ controller with pole placement for n-joint rigid robotic manipulators is presented. With linearization around the equilibrium manifold, the robotic system is transformed into a continuous linear parameter-varying (LPV) system with respect to the equilibrium manifold. A filter is introduced to obtain an augmented system, which is apt to have the polytopic gain scheduled controller designed. This system is put into a polytopic expression by a convex decomposition. Based on the concepts of quadratic D-stability and quadratic H∞ performance, the polytopic features are used to simplify the controller design to be a vertices’ controller design for the polytope. A state feedback gain, which satisfies H∞ performance and dynamic characteristics for each vertex of the polytope, is designed with a Linear Matrix Inequality (LMI) approach. A global continuous gain scheduled controller is then obtained by a synthesis of the vertex gains. Experiments demonstrate the feasibility of the designed controller.

The influence of ground irregularities on the behavior of a wheeled mobile robot (WMR) navigating on uneven surfaces is addressed. The paper studies the vibratory movements induced on the body of the WMR, in order to analyze its ability for carrying out on-board tasks, and on the accuracy of the data collected by its external sensorial systems. The adhesion capability of the wheels of the WMR on this uneven terrain is also studied, since it conditions the braking, traction and steering performance. The method is applied to the WMR RAM.

Two key aspects of most living organisms is their ability to detect and exploit natural sources of energy within their environment. We are currently developing a robotic system that will attempt to sustain itself by hunting and catching slugs on agricultural land. A microbial fuel cell will be used to convert the slug bio-mass to electricity thus providing the robot's energy supply. This paper outlines the requirements for such a predator and describes the entire robot. Data is also presented from trials of the robot hunting and catching slugs in a situation similar to that found in agricultural fields.

A novel hyper-redundant manipulator named RT1 is presented in this paper. The key feature of RT1 is that all degrees of freedom (DOF) are actuated with only one motor, via specially designed hinge bar universal joints. The mechanism of RT1 which includes a special hinge bar universal joint, bend structure and motion diversion structure is described. RT1 is a discrete manipulator; the discrete working space is described, and the parameter optimization for kinematical redundancy resolution is also studied. In selecting the unit increment of joints angles as an optimizing parameter, the criterion used is to alter the design parameter as little as possible during the manipulator’s motion from the initial to the expected position.

Low cost automation often requires accurate positioning. This happens whenever a vehicle or robotic manipulator is used to move materials, parts or minerals on the factory floor or outdoors. In last few years, such vehicles and devices are mostly autonomous. This paper presents the method of sensor fusion based on the Adaptive Fuzzy Kalman Filtering. This method has been applied to fuse position signals from the Global Positioning System (GPS) and Inertial Navigation System (INS) for the autonomous mobile vehicles. The presented method has been validated in 3-D environment and is of particular importance for guidance, navigation, and control of mobile, autonomous vehicles. The Extended Kalman Filter (EKF) and the noise characteristic have been modified using the Fuzzy Logic Adaptive System and compared with the performance of regular EKF. It has been demonstrated that the Fuzzy Adaptive Kalman Filter gives better results (more accurate) than the EKF. The presented method is suitable for real-time control and is relatively inexpensive. Also, it applies to fusion process with sensors different than INS or GPS.

The paper deals with on-line obstacle avoidance in an unstructured environment based on the force strategy. The obstacle avoidance is considered as a control problem. We discuss three approaches regarding the sensors used to detect the obstacles. First we investigate how obstacles can be avoided without using any sensors to detect them. To solve the problem we make use of a very basic principle: an action causes a reaction. For backdrivable manipulators we propose a controller which ensures stiff behaviour in the task space and compliant behaviour in the null space. Using such control the tracking capabilities in the task space can be preserved and the redundant degrees of freedom are used to avoid the obstacle after the collision. The tactile sensors are proposed to be used as the alternative for stiff systems. A tactile sensor detects an obstacle and the controller generates the avoiding motion. Last, we present a virtual forces approach which can be applied to the systems with proximity sensors. The objective is to assign each point on the body of the manipulator, which is close to the obstacle force component in a direction that is away from the obstacle. The proposed formulation avoids the problem of singular configurations and is very suitable when many obstacles are present in the neighbourhood of the manipulator. The computational efficiency of the proposed algorithms allows real-time application in a unstructured or time-varying environment. The efficiency of the proposed control algorithms is illustrated by simulations of highly redundant planar manipulators and by experiments on a four link planar manipulator.

A method for the time suboptimal control of an industrial manipulator that moves along a specified path while keeping its end-effector orientation unchanged is proposed. Nonlinear system equations that describe the manipulator motion are linearized at each time step along the path. A method which gives control inputs (joint angular velocities) for time suboptimal control of the manipulator is developed. In the formulation, joint angular velocity and acceleration limitations are also taken into consideration. A six degree of freedom elbow type manipulator is used in a case study to verify the method developed.

The Rehabilitation Technologies Division of Applied Resources Corp. (RTD-ARC) has engaged in a Phase I effort to commercialize a robotic bi-manual therapy machine for use in stroke rehabilitation, in cooperation with the VA Rehabilitation R&D Center in Palo Alto. The robotic therapy device, called ARCMIME here in order to differentiate it from its clinical predecessor, has the potential to improve rehabilitation outcomes significantly for individuals who have upper limb impairments due to stroke and other brain injuries.

This paper describes design considerations and clinical outcomes with regards to the Phase I system. It was found that the kinematically simpler system adequately replicated the data outcomes of the more sophisticated PUMA-based experimental test rig.

This paper concerns the presentation and analysis of a type of three translational degrees of freedom (DoFs) parallel cube-manipulator. The parallel manipulators are the topology architectures of the DELTA robot and Tsai's manipulator, respectively, which have three translational DoFs. In the design, the three actuators are arranged according to the Cartesian coordinate system, which means that the actuating directions are normal to each other, and the joints connecting to the moving platform are located on three sides of a cube, for such reason we call this type of manipulator the parallel cube-manipulator. The kinematics problems, singularity, workspace, compliance characteristic of the manipulator are investigated in the paper. The analysis results show that the manipulators have the advantages of no singularities in the workspace, relatively more simple forward kinematics, and existence of a compliance center. The parallel cube-manipulator can be applied to the fields of micro-motion manipulators, remote center compliance (RCC) devices, assembly, and so on.

This paper is concerned with a stability theory of motion governed by Lagrange's equation for a pair of multi-degrees of freedom robot fingers with hemi-spherical finger ends grasping a rigid object under rolling contact constraints. When a pair of dual two d.o.f. fingers is used and motion of the overall fingers-object system is confined to a plane, it is shown that the total degree of freedom of the fingers-object system is redundant for realization of stable grasping though there arise four algebraic constraints. To resolve the redundancy problem without introducing any other extra and artificial performance index, a concept of stability of motion starting from a higher dimensional manifold to a lower-dimensional manifold, expressing a set of states of stable grasp with prescribed contact force, is introduced and thereby it is proved in a rigorous way that stable grasp in a dynamic sense is realized by a sensory feedback constructed by means of measurement data of finger joint angles and the rotational angle of the object. Further, it is shown that there exists an additional sensory feedback that realizes not only stable grasp but also orientation control of the object concurrently. Results of computer simulation based on Baumgarte's method are presented, which show the effectiveness of the proposed concept and analysis.

This paper proposes an algorithm for managing redundant measurements provided by a stereo multi-camera system to achieve accurate visual tracking of a moving object. Selfocclusion, different visual resolution zones and optimal selection of redundant measurements are some of the problems addressed. The algorithm uses the extended Kalman filter embedded in a computational efficient pose estimation procedure based on Binary Space Partitioning Tree geometric modelling of 3D objects. Experimental results are presented for the case of an object moving in the visual space of two fixed cameras.

This paper intends to contribute to the study of dynamically balanced legged robots. A real-time applicable control algorithm for a planar one-legged robot is developed, which allows for locomotion on an irregular terrain. The simulated model consists of an articulated leg and a body, vertically placed upon the leg. During the stance phase the leg is supported by a massless foot. The algorithm is based on the choice of a number of objective locomotion parameters which can be changed from one hop to another. From a chosen initial configuration the robot is able to transfer to a chosen end configuration, while simultaneously controlling its forward velocity, its step length and its stepping height. The foot is thus being placed exactly on a chosen foothold. To reach this goal, the actuators track polynomial functions. The calculation of these functions is based on the objective parameters, and takes into account the constraints acting on the robot. These constraints result from the fact that during flight the center of gravity of the robot tracks a parabolic trajectory, and that the angular momentum with respect to the center of gravity is conserved. Writing the angular momentum constraint in a Caplygin form is the key to the algorithm. Promising simulation results for the algorithm are shown for two different experiments.

This work deals with the real-time robot control implementation. In this paper, an algorithm for solving Inverse Dynamic Problem based on the Gibbs-Appell equations is proposed and verified. It is developed using mainly vectorial variables, and the equations are expressed in a recursive form, it has a computational complexity of O(n). This algorithm will be compared with one based on Newton-Euler equations of motion, formulated in a similar way, and using mainly vectors in their recursive formulation. This algorithm was implemented in an industrial PUMA robot. For the robot control a new and open architecture based on PC had been implemented. The architecture used has two main advantages. First it provides a total open control architecture, and second it is not expensive. Because the controller is based on PC, any control technique can be programmed and implemented, and in this way the PUMA can work on high level tasks, such as automatic trajectory generation, task planning, control by artificial vision, etc.

The desert ant Cataglyphis is able to explore its desert habitat for hundreds of meters while foraging and return back to its nest precisely and in a straight line. With a body of less than 10 mm and a brain of less than one cubic millimeter they provide a challenge for hi-tech engineers. In this article, we give an overview of our attempts to model parts of its navigation behavior using robots and computer simulations. Inspired by the insect's navigation system we have developed mechanisms for path integration and visual piloting that were successfully employed on the mobile robot Sahabot 2.

The objective of the paper is to present a method of designing geometrical parameters of 3-dof orientation mechanisms. The parameters are to be determined for a given workspace, which in this case is described as a set of angles of orientation. An algorithm is presented, based on the equations of constraints which makes it possible to obtain the parameters of a manipulator. whose workspace involves the specified taskspace.

In path planning design, potential fields can introduce force constraints to ensure curvature continuity of trajectories and thus facilitate path-tracking design. The parametric thrift of fractional potentials permits smooth variations of the potential in function of the distance to obstacles without requiring design of geometric charge distribution. In the approach we use, the fractional order of differentiation is the risk coefficient associated to obstacles. A convex danger map towards a target and a convex geodesic distance map are defined. Real-time computation can also lead to the shortest minimum danger trajectory, or to the least dangerous of minimum length trajectories.

We propose a simple quasi time optimal control law for a gantry crane with a payload. The force applied to the trolley is a controlling parameter. The control law consists of two parts: a feedforward term and a trolley position and velocity feedback term.

Initially, we synthesize the feedforward term and the corresponding reference trajectory by computing the time optimal control for the system mass center. The computed optimal control is a discontinuous function of time with several switching time instants. Undesirable large vibrations due to the payload sway appear under this control. Therefore, we transform this control, replacing its jumps by the piecewise linear continuous functions. The computed feedforward term and the reference trajectory are used as input signals of the PD-controller.

This paper presents an investigation of odor localization by groups of autonomous mobile robots using principles of Swarm Intelligence. First, we describe a distributed algorithm by which groups of agents can solve the full odor localization task more efficiently than a single agent. Next, we demonstrate that a group of real robots under fully distributed control can successfully traverse a real odor plume, and that an embodied simulator can faithfully reproduce these real robots experiments. Finally, we use the embodied simulator combined with a reinforcement learning algorithm to optimize performance across group size, showing that it can be useful not only for improving real world odor localization, but also for quantitatively characterizing the influence of group size on task performance.