Planning a sequence of robot actions is especially difficult when the outcome of actions is uncertain, as is inevitable when interacting with the physical environment. In this paper we consider the case of finite state and action spaces where actions can be modeled as Markov transitions. Finding a plan that achieves a desired state with maximum probability is known to be an NP-Complete problem. We consider two algorithms: an exponential-time algorithm that maximizes probability, and a polynomial-time algorithm that maximizes a lower bound on the probability. As these algorithms trade off plan time for plan quality, we compare their performance on a mechanical system for orienting parts. Our results lead us to identify two properties of stochastic actions that can be used to choose between these planning algorithms for other applications.

This paper presents a systematic approach to the time-optimal motion planning of a cooperative two robot system along a prescribed path. First, the minimum-time motion planning problem is formulated in a concise form by parameterizing the dynamics of the robot system through a single variable describing the path. The constraints imposed on the input actuator torques and the exerted forces on the object are then converted into those on that variable, which result in the so-called admissible region in the phase plane of the variable. Considering the load distribution problem that is also involved in the motion, we present a systematic method to construct the admissible region by employing the orthogonal projection technique and the theory of multiple objective optimization. Especially, the effects of viscous damping and state-dependent actuator bounds are incorporated into the problem formulation so that the case where the admissible region is not simply connected can be investigated in detail. The resultant time-optimal solution specifies not only the velocity profile, but also the force assigned to each robot at each instant. Physical interpretation on the characteristics of the optimal actuator torques is also included with computer simulation results.

The influence of the angle between the axes of the peg and hole (angular error) and the contact surface defects on the measurement of deviation (lateral error) have been carefully analysed. It has been shown that they would influence the measurement of the magnitude of deviation and even its direction. This phenomenon causes severe difficulty in the assembly operations. A novel strategy for the high-precision chamferless peg hold insertion with a wrist force sensor is presented. This strategy is constructed: (1) to obtain the relationship between the peg and hole from the force sensor signal when an angle between the axes of the peg and hole exists and defects of the contact surfaces are present, (2) to reduce the angular and lateral errors, (3) to achieve the precise chamferless robotic peg hole insertion. In this paper, the insertion can be obtained with a reasonably large range of initial conditions. The principle is to move and rotate the peg from an area having many geometric uncertainties to a new area, where the deviation of the peg and hole can be obtained.

In this paper we propose some simple rules for PID tuning of robot manipulators. The procedure suggested requires the knowledge of the structure of the inertia matrix and the gravitational torque vector of the robot dynamics, but only upper bounds on the dynamics parameters are needed. This tuning procedure is extracted from the stability analysis by using a suitable Lyapunov function together with the LaSalle invariance principle. We show that with this guideline, the overall closed-loop system is asymptotically stable. This procedure is illustrated for a two degrees-of-freedom robot

The concept of tension is introduced and applied to a robot's trajectories, then new joint interpolation strategies are implemented. A joint interpolation strategy is proposed which uses joint variable reference data calculated from inverse kinematics, along with a polynomial equation or quintic equation as the parametric equation of the joint variables. This method can use any polynomial equation which has the C2 continuity property and has intermediate points which pass through the reference data. For the time variable, first order linear equations can be used where the number of equations is n – 1, n being the number of points in the reference data. Due to large reductions in computational burden resulting from this form, this method may be suited for real time applications.

A new neural network (NN) control technique for robot manipulators is introduced in this paper. The fundamental robot control technique is the model-based computed-torque control which is subjected to performance degradation due. to model uncertainty. NN controllers have been traditionally used to generate a compensating joint torque to account for the effects of the uncertainties. The proposed NN control approach is conceptually different in that it is aimed at prefiltering the desired joint trajectories before they are used to command the computed-torque-controlled robot system (the plant) to counteract performance degradation due to plant uncertainties. In this framework, the NN controller serves as the inverse model of the plant, which can be trained on-line using joint tracking error. Several variations of this basic technique is introduced; Back-propagation training algorithms for the NN controller have been developed. Simulation results have demonstrated the excellent tracking performance of the proposed control technique.

In the computational kinematics of robotic manipulators, accuracy and sensitivity of the results are highly dependent on the choice of the coordinate system, the metric system, and the appropriateness of performance evaluation measure. In this paper, these undesired sensitivities are examined and suitable performance criteria are developed to eliminate the coordinate system and metric system dependencies, and adverse numerical effects associated with them. Also a new formulation for the Jacobian matrix, joint velocities, and hand velocities, based on the Euler angles, is developed. This formulation, further improves numerical accuracy of the computations. Numerical experiments are included.

A new approach to represent assembly called state matrix representation and an algorithm for automatic robot assembly planning based on this representation is proposed. The state matrix representation of assembly is configured by considering the inter-relationships of parts and objects involved in the initial and the goal structures. Thanks to this new representation, the planning lgorithm is straightforward and can be easily and efficiently implemented with simple matrix manipulation. Unlike other planning methods, the actions involved in the assembly process are not defined in advance but are generated at planning time. The syntax of actions are designed so that while directly reflecting the semantics of actions, they can be easily manipulated by the planner. Two examples of how to plan an assembly based on this representation are given in the paper.

An algorithm for the motion planning of the multifingered hand is proposed to generate finite displacements and changes in orientation of objects by considering sliding contacts as well as rolling contacts between the fingertip and the object at the contact point. Specifically, a nonlinear optimization problem is firstly formulated and solved to find the minimum joint velocity and the minimum contact force to impart a desired motion to the object at each time step. Then, the relative velocity at the contact point is found by calculating the velocity of the fingertip and the object at the contact point. Finally, time derivatives of the surface variables and the contact angle of the fingertip and the object at the current time step is computed using the Montana's contact equation to find the contact parameters of the fingertip and the object at the next time step. To show the validity of the proposed algorithm, a numerical example is illustrated by employing the robotic hand manipulating a sphere with three fingers each of which has four joints

A dynamic model for two three-link cooperating structurally-flexible robotic manipulators is presented in this study. The equations of motion are derived using the extended Hamilton's principle and Galerkin's method, and must satisfy certain geometric constraints due to the closed chain formed by the two manipulators and the object. The dynamic model presented here is for the purpose of designing controllers. Therefore, a low-order model which captures all the major effects is of interest. Computer simulated results are presented for the case of moving an object along an elliptical path using the two cooperating flexible manipulators.

Structural and control flexibilities affect the absolute precision of serial manipulators. A semi-flexible kinematic model is developed, to improve the absolute static precision. It expands the solid body model by incorporating a spring effect for each joint and a beam effect for each link. Simulation results confirm the adequacy of the model. The dependencies existing between the articulate posture of the manipulator, the effects of the external efforts and the gravitational load on the global structure are properly described. The identifiability of the added parameters is explored on a RR planar robot. It requires efforts and pose errors to be known in the tool frame only.

A new mathematical formulation of robot and obstacles is presented such that for on-line collision recognition only robot joint positions in the workspace are required. This reduces calculation time essentially because joint positions in workspace can be computed every time from the joint variables through robot geometry. It is assumed that the obstacles in the workspace of the manipulator are represented by convex polygons. For every link of the redundant robot and every obstacle a boundary ellipse is defined in workspace such that there is no collision if the robot joints are outside this ellipsis.

In addition to this, a collision avoidance method is presented which allows the use of redundant degrees of freedom such that a manipulator can avoid obstacles while tracking the desired end-effector trajectory. The method is based on the generalized inverse with boundary ellipse functions as optimization criteria. The method permits the tip of the hand to approach any arbitrary point in the free space while the kinematic control algorithm maximizes the boundary ellipse function of the critical link. The effectiveness of the proposed methods is discussed by theoretical considerations and illustrated by simulations of the motion of three- and four-link planar manipulators between obstacles.

The pulsed time-of-flight laser rangefinding technique has been used in many industrial measurement applications, including 3D-coordinate measuring devices, hot surface profilers and mobile robot sensors. Optical fibres, typically 1–10 m in length and 100–400 μm in diameter can be used to guide optical pulses to the separate sensing head of the measurement device. The use of a large multimode fibre may cause problems, however, when aiming at millimetre accuracy, as the construction and adjustment of the optics of the sensor head may affect the transit time linearity and measurement accuracy via multimode dispersion. Environmental effects, such as bending, vibration due to the moving sensing head and temperature, also cause measurement errors. The error sources are studied and characterized in this paper.

This paper presents two adaptive schemes for controlling the end-effector compliance of robot manipulators. Each controller possesses a decentralized structure, in which the control input for each configuration degree-offreedom (DOF) is computed based on information concerning only that DOF. The first scheme is developed using an adaptive impedance control approach and consists of two subsystems: a simple “filter” which modifies the end-effector position trajectory based on the sensed contact force and the desired dynamic relationship between the position and force, and an adaptive controller that produces the joint torques required to track this modified trajectory. The second compliant motion control strategy is an adaptive admittance controller for position-controlled manipulators. In this scheme a desired contact force is specified and then position setpoints for the “inner-loop” position controller are generated which ensure that this desired force is achieved. The proposed controllers are extremely simple computationally, do not require knowledge of the manipulator dynamic model or parameter values of the manipulator or the environment, and are implemented in decentralized form.

This paper presents a novel approach to designing and manufacturing of a universal gripper to be used with industrial robots in flexible assembly systems. Important issues that impact greatly on the efficiency of the gripper are also discussed in this paper. Such issues include the degree of compliance allowed by the robotic wrist and the way these grippers are actuated. The gripper has been proven to be extremely flexible and low in cost.

The dynamic model of a new class of underwater robot is derived and the validity of the model is checked experimentally. Close agreements between theory and experiment are attained. The interaction between the buoyancy and gravity forces acting on the robot arm, present in the underwater environment, is used to generate torques necessary to move the arm. The mathematical model of a multi-arm robot is developed to define the interaction between the dynamics of the moving weight and the robot links under the action of the resisting water drag and other external forces. The Lagrangian method is used in the formulation of the arm dynamics. The developed dynamic equations serve as means for designing the control laws necessary for controlling the position of the different joints of the robots. The study indicates that the buoyancy and gravity-driven robot can position a payload accurately as well as at a fairly fast speed of response. It is indicated from the theoretical and experimental study that the arm motion is created by a small displacement of moving weight on the power screw. Therefore, power requirement of this type of robot is just as enough to overcome the friction between the power screw and the moving weight. This features emphasize the potential of the concept as a viable means for driving underwater robots

This paper aims at contributing to a sub-symbolic, feedback-based “theory of robotic grasping” where no full geometrical knowledge of the shape is assumed. We describe experimental results on grasping 2D generic shapes without traditional geometrical processing. Grasping algorithms are used in conjunction with a vision system and a robot manipulator with a three-fingered gripper is used to grasp several different shapes. The altorithms are run on the shape as it appears on the computer screen (i.e. directly from a vision system). Simulated gripper ringer with virtual sensors are configured and positioned on the screen whose inputs are controlled by moving their position relative to the image until an equilibrium is reached among the control systems involved.

When an object is held by a multi-fingered hand, the values of the contact forces can be multivalued. An objective function, when used in conjunction with the frictional and geometric constraints of the grasp, can however, give a unique set of finger force values. The selection of the objective function in determining the finger forces is dependent on the type of grasp required, the material properties of the object, and the limitations of the röbot fingers. In this paper several optimization functions are studied and their merits highlighted. The paper introduces a graphical representation of the finger force values and the objective functions that enable one to select and compare various grasping configurations. The impending motion of the object at different torque and finger force values are determined by observing the normalized coefficient of friction plots.

This paper deals with the first transatlantic experiment of robotic telesurgery. A robot in Milan (Italy) performed an operation on a model of a pig, and the surgeon controller was in JPL, Pasadena (USA). By means of two communication satellites and of an optical fibre network, the robot performed a biopsy and a preliminary cut for a laparoscopic mini-invasive surgery operation.

In disassembly tasks, due to the large variety of objects and the different positions and orientations in which they appear, the disassembly trajectories supplied on-line by a human operator or an automatic recognition system can contain large errors. The classical compliant control methods turn out to be insufficient to eliminate sticking which is due to these errors. This paper presents a compliant control method for disassembly of non-elastic parts in non-elastic environments which adopts the trajectories according to realised motion. In case of sticking a new direction of motion is searched for until the manipulated part is set into motion.