Task Trajectory Research Articles

Online Trajectory Planning and Force Control for Automation of Surgical Tasks

Automation of surgical tasks is expected to improve the quality of surgery. In this paper, we address two issues that must be resolved for automation of robotic surgery: online trajectory planning and force control under dynamic conditions. By leveraging demonstrations under various conditions, we model the conditional distribution of the trajectories given the task condition. This scheme enables generalization of the trajectories of spatial motion and contact force to new conditions in real time. In addition, we propose a force tracking controller that robustly and stably tracks the planned profile of the contact force by learning the spatial motion and contact force simultaneously. The proposed scheme was tested with bimanual tasks emulating surgical tasks that require online trajectory planning and force tracking control, such as tying knots and cutting soft tissues. Experimental results show that the proposed scheme enables planning of the task trajectory under dynamic conditions in real time. In addition, the performance of the force control schemes was verified in the experiments. Note to Practitioners —This paper addresses the problem of motion planning and control for automation of surgical tasks. In surgical tasks, it is necessary to manipulate objects under conditions where positions or shapes of objects often change during the task. Thus, trajectories for surgical tasks need to be planned and updated according to the change in the conditions in real time. In this paper, we propose a framework for learning both spatial motion and force profile from human experts. The proposed system can plan and update task trajectories in real time and robustly control the contact force under dynamic conditions. On the other hand, generalization of trajectories is limited to the conditions, which are close to the conditions where the demonstrations were performed. In the future work, we will investigate reinforcement learning approaches in order to enable autonomous improvement of the performance.

Safety in human-multi robot collaborative scenarios: a trajectory scaling approach

In this paper, a strategy to handle the human safety in a multi-robot scenario is devised. In the presented framework, it is foreseen that robots are in charge of performing any cooperative manipulation task which is parameterized by a proper task function. The devised architecture answers to the increasing demand of strict cooperation between humans and robots, since it equips a general multi-robot cell with the feature of making robots and human working together. The human safety is properly handled by defining a safety index which depends both on the relative position and velocity of the human operator and robots. Then, the multi-robot task trajectory is properly scaled in order to ensure that the human safety never falls below a given threshold which can be set in worst conditions according to a minimum allowed distance. Simulations results are presented in order to prove the effectiveness of the approach.

Identification of activities of daily living in tremorous patients using inertial sensors

Tremor and voluntary movement of the upper limb are separated from IMUs signals.Seven daily living tasks are classified with an accuracy of 86%.Grain (precise or gross) of daily living tasks is identified with 79% accuracy.Direction (distal/ proximal) of daily living tasks is identified with 89% accuracy.Tremor kinematics can be coupled with the kind of task where it appears. BACKGROUNDMuch attention has been given to the use of inertial sensors for remote monitoring of individuals suffering from neurological pathologies. However, the focus has been mostly on the detection of symptoms like tremor or dyskinesia, not on identifying specific activities carried out by subjects. The objective of this study was to develop an automated segmentation and recognition methodology, from inertial sensor data, to identify tasks and motor patterns during activities of daily living. This will enable clinicians to contextualize the symptoms of these diseases and improve their treatment. METHODSWe designed and tested a methodology to automatically label continuous upper-limb activity from IMUs (Inertial Measurement Units). Three classification problems are considered: the task itself, the precision level required by the task with respect to movement (fine or gross) and the trajectory of the task (distal or proximal). These problems were identified by tremor experts as clinically important aspects to be monitored in tremor patients while performing daily activities. The proposed methodology reveals the relation between the functional context or activity and the patient's on-going tremor to clinicians. RESULTSOverall task identification rate was 86%. Task precision and task trajectory are classified with 79% and 89% accuracy, respectively. Aligning the semantic nature of the activity with the tremor location and intensity can also provide novel and relevant information for clinical monitoring of tremor and help clinicians and researchers as a useful tool to develop new therapies or strategies and novel anti-tremor medications to combat context dependent tremor. CONCLUSIONSThe present study describes the development of a comprehensive methodology based on machine learning techniques to segment and detect activities of daily living in people with tremor using inertial sensors, which aims at facilitating detailed interpretation of tremor movements by neurologists.

Modelling and control of an upper extremity exoskeleton for rehabilitation

This paper presents the modelling and control of a two degree of freedom upper extremity exoskeleton for rehabilitation. The Lagrangian formulation was employed to obtain the dynamic modelling of both the anthropometric based human upper limb as well as the exoskeleton that comprises of the upper arm and the forearm. A proportional-derivative (PD) architecture is employed to investigate its efficacy performing a joint task trajectory tracking in performing flexion/extension on the elbow joint as well as the forward adduction/abduction on the shoulder joint. An active force control (AFC) algorithm is also incorporated into the aforementioned controller to examine its effectiveness in compensating disturbances. It was found from the study that the AFC-PD performed well against the disturbances introduced into the system without compromising its tracking performances as compared to the conventional PD control architecture.

Task based synthesis of serial manipulators

Computing the optimal geometric structure of manipulators is one of the most intricate problems in contemporary robot kinematics. Robotic manipulators are designed and built to perform certain predetermined tasks. There is a very close relationship between the structure of the manipulator and its kinematic performance. It is therefore important to incorporate such task requirements during the design and synthesis of the robotic manipulators. Such task requirements and performance constraints can be specified in terms of the required end-effector positions, orientations and velocities along the task trajectory. In this work, we present a comprehensive method to develop the optimal geometric structure (DH parameters) of a non-redundant six degree of freedom serial manipulator from task descriptions. In this work we define, develop and test a methodology to design optimal manipulator configurations based on task descriptions. This methodology is devised to investigate all possible manipulator configurations that can satisfy the task performance requirements under imposed joint constraints. Out of all the possible structures, the structures that can reach all the task points with the required orientations are selected. Next, these candidate structures are tested to see whether they can attain end-effector velocities in arbitrary directions within the user defined joint constraints, so that they can deliver the best kinematic performance. Additionally least power consuming configurations are also identified.

Adaptive fuzzy controller for controlling the dynamics of robot motion

Autonomous robots are of prime importance in everyday life because of their capability to handle the non-linear situations. This paper describes the autonomous robot motion control system based on fuzzy logic proportional integral (PI) controller that reaches to its target value faster than others. Fuzzy rules are embedded in the controller to tune the gain parameters of PI controller and to move the robot along the task trajectory with variation in heading angle (θ) towards the target to make it helpful in real time applications. It discusses the design aspects of the fuzzy PI controller for controlling the dynamics of autonomous robot that have higher distribution rejection properties (DRP), low settling time (ST) and high adaptability towards the variation in the angle towards the target. The performance of a robot (RM) has been verified using MATLAB and results obtained have been found to be robust. Overall, the performances criteria in terms of its response towards ST, target acquisition (TA) and DRP have been found to be good.

Children’s competence or adults’ incompetence: Different developmental trajectories in different tasks.

Dual-process theories have been proposed to explain normative and heuristic responses to reasoning and decision-making problems. Standard unitary and dual-process theories predict that normative responses should increase with age. However, research has focused recently on exceptions to this standard pattern, including developmental increases in heuristic or intuitive responses. Developmental trends for normative and heuristic responses were investigated for 2 kinds of causal reasoning (if-only and covariation) problems in 2 experiments. To investigate the role of superstitious thinking in these developmental trends, in both experiments a superstitious element was added to the problem solved by half the participants. In the first experiment, 90 fifth graders, 99 seventh graders, and 153 adults responded to an if-only problem. Children performed better than adults, with normative responses decreasing and heuristic responses increasing with age. A superstitious jinx intended to reduce heuristic responses had little effect for all age groups. In the second experiment, 276 fifth graders, 344 seventh graders, and 90 adults responded to a covariation-detection problem. When win-loss ratios were equal, adults performed better than children, with normative responses increasing and heuristic responses decreasing with age. When win-loss ratios were strikingly different, however, even the youngest children were able to solve the problems correctly; participants of all ages responded about equally well. When the normative response required recognizing that a good-luck ritual led to better team performance, participants in all age groups responded skeptically that the ritual had no effect, illustrating belief bias. These results are discussed in terms of dual-process theories and the development of heuristic (or intuitive) and analytical processes.

Colour Correspondence Effects between Controlled Objects and Targets

It is increasingly popular to use movement trajectories as a measure of mental processes related to task performance. Often this is accomplished by moving a cursor to a target on a computer screen. However, the relation between features of the cursor and the targets is rarely, if at all, considered. In five experiments, we examined whether moving a cursor to a target was affected by the relation between their colours, even when this relation was task irrelevant. In Experiments 1-3, a mouse-controlled cursor was moved to one of two coloured targets. Results showed colour correspondence effects in latency to initiate a response, duration of movement times, and movement trajectories when the relationship between cursor and target colours was task relevant (Experiment 1) and when only the cursor colour was task relevant (Experiment 2), but not when only the target was task relevant (Experiment 3). Follow-up experiments using single targets showed that colour correspondence effects occurred as long as attention was dedicated to the colour of the cursor, even when neither the cursor nor the target colour was relevant to selecting the correct movement (Experiments 4 and 5). Furthermore, when the relation between cursor and target colours is task irrelevant, colour correspondence effects for response initiation times are uncorrelated with those for movement times and movement trajectories. We interpret the observed correspondence effect in terms of response coding, although attention cueing may also play a role, and suggest that greater consideration of cursor features is needed when examining movement trajectories in choice reaction tasks.

A statically balanced SCARA-like industrial manipulator with high energetic efficiency

The purpose of the work is the improvement of the energetic efficiency of automated lines assisted by four-degree-of-freedom serial robots with three translations and one rotation about a vertical axis (Schoenflies motion). A novel robotic architecture (BalArm) has been designed. It is derived from a RRPR SCARA by substituting a four-bar mechanism for the vertical prismatic joint, in order to balance statically the robot by means of a counter-weight or a torsional spring. The kinematic and dynamic models of the manipulator are described. Using these models, different typical pick-and-place operations have been simulated; the results show that for low-speed motions the mass balancing is more efficient, while for high-speed motions the elastic balancing is preferable; the advantage threshold depends on the task trajectory, speed and acceleration and on the preload of the elastic element. From a constructive point of view, the BalArm robot can be realized with modular solutions, in order to easily change the static balancing. This allows to adapt the balancing to the specific working cycle to minimise the energy consumption, with potential economical and environmental benefits.

A model for predicting pathologist's velocity profiles when navigating virtual slides

Navigation through large microscopic images is a potential benefit for histology or pathology teaching, for improving the quality of diagnosis in pathology, or for communicating pathologists in some telemedicine applications. However, the size of this kind of images is prohibitive for navigation with conventional techniques. This article presents a soft computing model, which permits to anticipate the pathologist trajectories in diagnosis tasks when exploring virtual slides. The Bayesian strategy combines an offline model of a baseline pathologist knowledge (the prior) and a prediction online module (the likelihood) that captures a particular pathologist navigation pattern. While optimal parameters for the biologically inspired offline model are calculated using an Expectation-Maximization strategy, prediction is carried out by a particle filter. Parameters are estimated from several series of actual navigations performed by several pathologists in different virtual slides. The present approach is compared with other conventional prediction methods and decreases the calculated MSE in about a 50% for the entire group of pathologists.

An Adaptive Automated Robotic Task-Practice System for Rehabilitation of Arm Functions After Stroke

We present a novel robotic task-practice system, i.e., adaptive and automatic presentation of tasks (ADAPT), which is designed to enhance the recovery of upper extremity functions in patients with stroke. We designed ADAPT in accordance with current training guidelines for stroke rehabilitation; ADAPT engages the patient intensively, actively, and adaptively in a variety of realistic functional tasks that require reaching and manipulation. A general-purpose robot simulates the dynamics of the functional tasks and presents these functional tasks to the patient. A novel tool-changing system enables ADAPT to automatically switch between the tools corresponding to the functional tasks. The control architecture of ADAPT is composed of three main components: a high-level task scheduler, a functional task model, and a low-level admittance controller. The high-level task scheduler adaptively selects the task to practice and sets the task difficulty based on the previous performance of the patients. The functional task model generates desired trajectories based on learned models of task dynamics. Tasks dynamics are modeled with receptive field weighted regression (RFWR), such that the feel of the task tools is accurately modeled, and the task difficulty can be easily adjusted. The low-level admittance controller <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">,</i> which is also learned with RFWR <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">,</i> implements the selected task trajectory for robot-patient interaction. The results of a preliminary experiment with a healthy subject demonstrate the successful operation of ADAPT.

On Giving Hegel His Due

It has been Hegel's ironic fate to have been, at once, both greatly overestimated and seriously underestimated. On the one hand, the figure of Hegel has been fantastically inflated into something like an Oedipal father whose children must slay him at any cost in order to attain their own distinctive voices.' On the other hand, especially with respect to his claim to have the of the Concept, he has been either ignored or accused of irresponsible hyperbole.2 The view I wish to outline in this essay is contrarian on both counts, seeking rather to give Hegel his due, which means both no more and no less than he deserves. In this essay, I will suggest, on the one hand, that Hegel's principal historical contribution was to have accomplished no more than bringing to the project, first suggested by Kant, of offering a full systematic account of the fundamental determinations of Reason. On the other hand, I will claim that this resulted in no less than a fundamental and far-reaching change of trajectory in the of philosophy. Put in other terms, I will suggest that Hegel's philosophy both ended the pre-Hegelian tradition's project of conceptually unifying and oppositions and, at the same time, commenced the post-Hegelian project of differences in the face of overarching unities or totalities. Central to my argument will be the claim that, like Kant, Hegel viewed the philosophical of the tradition preceding him (hence traditional philosophy itself) as limited, and that he assumed, also like Kant, that it is only when these limits are demonstrated and acknowledged that new post-traditional projects can begin to be defined. Put once more, I will suggest that philosophy after Hegel becomes capable of confronting its others (or that which is different from philosophy itself) only when it has acknowledged its own intrinsic limitations, when the of the Concept has, indeed, been acknowledged as having ended-that is, when Hegel has finally been given his due.3 My argument will unfold in the following manner. I will begin by suggesting that Hegel's claim about ending the of the Concept must be taken in full seriousness, but only on an understanding of this claim that acknowledges its own limited scope. More specifically, I will attempt to show that, as Hegel himself insisted, this claim must always be understood in connection with the project of the Science of Logic and not the broader system. I will then consider how the completion of Reason entailed a radical change in trajectory or redirection of the fundamental tasks of philosophy, a change that we might gloss as that from constructing conceptual unities to saving and exploring differences. As evidence for this change, I will offer a brief characterization of post-Hegelian philosophy. I will also suggest why the simultaneous over- and under-estimating of Hegel's accomplishment typical of so much post-Hegelian philosophy has served as a major hindrance both to delineating its projects and making significant headway with them. I will conclude by sketching, on the basis of Hegel's own thought, how the fundamental projects of post-Hegelian philosophy can emerge in forms that do not require the dissociation from the tradition (and Hegel) insisted upon by the obsessive anti-Hegelianism so characteristic of most post-Hegelian thought. The Completion of in Hegel's Philosophy For subscribers to the line of thought that might be called obsessive anti-Hegelianism, it might come as a surprise that, at least as concerns philosophy, the idea of an of history was first suggested by that most humble apostle of the limited capacities of Reason, Immanuel Kant. In the remarkable and almost universally ignored final paragraph of the Critique of Pure Reason, Kant proposes that, with a little help from the friends of the Critical philosophy, it may be possible to achieve before the end of the present century what many centuries have not been able to accomplish; namely, to secure for human reason complete satisfaction in regard to that with which it has all along so eagerly occupied itself, though hitherto in vain. …

Inverse Kinematics of Multilink Flexible Robots for High-Speed Applications

A straightforward inverse kinematic algorithm for multilink flexible robots is proposed to improve the control performance. The inclusion of a dynamic constraint maximizes the performance of feedback controllers in high-speed applications. To obtain a numerically feasible solution, the singular perturbation approach is employed, which decomposes the inverse kinematics into an averaged part (slow part) and a parasitic part (fast part). The solution of the averaged part is considered the desired inverse kinematics, while the parasitic part is intentionally removed. The parameter expansion is carried out to obtain the solution sequentially. The implicit expansion method, which is a refined version of the expansion method, reduces computing time considerably. The formula in discrete time offers efficiency in computer applications. In addition, a requirement on differentiability of the desired task trajectory is derived.

Task Oriented Optimum Positioning of a Mobile Manipulator Base in a Cluttered Environment

A method for generating discrete optimal sequences of base locations for mobile manipulators is presented that considers the task capability of the workspace in a cluttered environment. In implementation, the obstacles and task trajectories are represented by 2^n trees, so that a series of set operations are performed to characterize the manipulator’s configuration space into topological subspaces. By incorporating trajectory-motion-capable subspaces into the enumeration of the cost function, an optimum search technique is made applicable to the determination of a task feasible location. The method is then extended to a multiple positioning problem by concatenating the single optimization processes into a serial multistage decision making system, for which an optimal set of decisions can be found through a computationally efficient dynamic programming process. The computational paradigm of the present method is coherent with topological workspace analysis, and thus applicable to task trajectories of arbitrary dimensions and shapes. The effectiveness of the presented method is demonstrated through simulation studies performed for a 3-d.o.f. regional manipulator operating under various task conditions.

Designing Fault-Tolerant Manipulators: How Many Degrees of Freedom?

One of the most important parameters to consider when de signing a manipulator is the number of degrees of freedom (DOFs). This article focuses on the question: How many DOFs are necessary and sufficient for fault tolerance, and how should these DOFs be distributed along the length of the manipula tor ? A manipulator is fault tolerant if it can complete its task even when one of its joints fails and is immobilized. The num ber of DOFs needed for fault tolerance strongly depends on the knowledge available about the task. In this article, two approaches are explored. First, for the design of a general purpose fault-tolerant manipulator, it is assumed that neither the exact task trajectory nor the redundancy resolution algo rithm are known a priori and that the manipulator has no joint limits. In this case, two redundant DOFs are necessary and sufficient to sustain one joint failure, as is demonstrated in two design templates for spatial fault-tolerant manipulators. In a second approach, both the Cartesian task path and the redundancy resolution algorithm are assumed to be known. The design of such a task-specific fault-tolerant manipulator requires only one degree of redundancy.

A recurrent neural network-based adaptive variable structure model-following control of robotic manipulators

A novel scheme for integrating a neural network approach with an adaptive implementation of variable structure control for multijointed robotic manipulators in complex task executions is presented. The control strategy is developed within the general framework of nonlinear model-following control and attempts to minimize the total regulation time while ensuring a specified percentage of time on the sliding manifolds in order to exploit the disturbance attenuation features present during the sliding motions. These objectives are realized by tailoring an adaptation process that appropriately adjusts the controller gains to keep the motion on the sliding manifolds and also progressively updates the sliding manifold parameters. Rapid execution of the adaptation process is facilitated by a multilayer recurrent neural network. The resulting control scheme is decentralized, and permits design of independent joint controls. A quantitative performance evaluation of the neural network-based adaptive variable structure controller is given in several task scenarios, namely regulation, trajectory tracking and model-following.

Robotic manipulator control of generalized contact force and position

Considers the problem of control of generalized contact forces with a manipulator controller that has traditionally been regarded as a noncontact task trajectory controller. The open-loop control of generalized forces, suitable for tasks in which only crude force control is required, is achieved through the manipulation of the generalized position inputs of the robotic manipulator. An algorithm is proposed which determines the appropriate manipulator generalized inputs, the only input signal available to the position controller, in order to generate prescribed generalized force and position trajectories during contact with the robot work environment. During noncontact motion of the manipulator, the robot is operated in the more usual generalized position control mode. The use of such a method to control generalized contact forces, although in an open-loop manner, permits a single control to be utilized for both noncontact and contact tasks. Thus, issues of stability during the transition to and from contact, as well as stability during sustained contact are avoided. Hence, the utilization of a single control for both noncontact and contact phases of a single task is seen to be advantageous. The stability of the robotic manipulator during object contact, implicitly assumed by the proposed control strategy, is established using the theory of singular perturbations. Experimental results of a two-degree-of-freedom direct drive manipulator during contact with a one-degree-of-freedom linear mechanical impedance illustrate the usefulness of the proposed method.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Human Manipulative Skill Analysis and Acquisition for the Intelligent Assisting System

In this paper we propose a new forthcoming research topic the Intelligent Assisting System IAS. Using this system we want to approach the identification and analysis of human manipulation skills to be used for intelligent human operator assistance. A manipulation skill data base enables the IAS to perform complex manipulations on the motion control level. Through repeated interaction with the operator for unknown environment states, the manipulation skills in the data base can be increased on-line. A model for manipulation skill based 011 the grip transformation matrix is proposed, which describes the transformation between the object trajectory and contact conditions. The dynamic behavior of the grip transform is regarded as the essence of the performed manipulation skill. We describe the experimental system setup of a skill acquisition and transfer system as a first approach to the IAS and some results confirming the calibration method of the developed sensor glove. A simple manipulation example shows the feasibility of the proposed manipulation skill model. Further this paper defines a control algorithm realizing object task trajectories and its feasibility is shown by simulation.

The Development of a Direct Drive Master Arm

This paper deals with the development of a 4 degree of freedom direct drive master manipulator system which has the ability of virtually adjusting its mechanical impedance. In the field of bilateral master-slave manipulation, there are some important points to be considered when a master manipulator is designed. One point is related to how to measure the human operator’s arm motion with high accuracy (which the operator produces to teach the trajectory of tasks). Another point is how to design an effective force/torque generator to make an operator feel the constraint forces the slave arm will receive from the environments during tasks. To satisfy these requirements, a manipulator with a variable mechanical impedance structure and joints equipped with high resolution angular displacement sensors is expected to be developed. The use of the variable impedance structure provides a capability of reflecting the constraint forces to an operator not only statically, but also dynamically. This is effective to present the constraints to an operator with high fidelity. In the research, joint mechanisms and joint sensors suitable for the impedance control were discussed, while the mechanical structure of the master manipulator which is effective to construct a simple impedance control law was investigated. With these considerations in mind, a master manipulator was designed and its impedance control law was formulated. The features of the manufactured manipulator are summarized as follows; (1) each joint is driven by a direct drive torque motor with less friction and has a high resolution angular encoder attached to a processor which can provide joint angular displacement, angular velocity and angular acceleration. (2) the manipulator has the decoupled and configuration-invariant inertia structure in part which is effective to simplify impedance control law. In the paper, the design concept of the master manipulator is first discussed. Secondly, the details of the manufactured manipulator structure are explained. Finally, the results of the evaluation experiments are described and the fundamental characteristics of the system are confirmed.

Improved configuration control for redundant robots

AbstractThis article presents a singularity‐robust task‐prioritized reformulation of the configuration control scheme for redundant robot manipulators. This reformulation suppresses large joint velocities near singularities, at the expense of small task trajectory errors. This is achieved by optimally reducing the joint velocities to induce minimal errors in the task performance by modifying the task trajectories. Furthermore, the same framework provides a means for assignment of priorities between the basic task of end‐effector motion and the user‐defined additional task for utilizing redundancy. This allows automatic relaxation of the additional task constraints in favor of the desired end‐effector motion, when both cannot be achieved exactly. The improved configuration control scheme is illustrated for a variety of additional tasks, and extensive simulation results are presented.