Full Robot Research Articles

Mobile robot navigation with a self-paced brain–computer interface based on high-frequency SSVEP

SUMMARYA brain–computer interface (BCI) is a system for commanding a device by means of brain signals without having to move any muscle. One kind of BCI is based on Steady-State Visual Evoked Potentials (SSVEP), which are evoked visual cortex responses elicited by a twinkling light source. Stimuli can produce visual fatigue; however, it has been well established that high-frequency SSVEP (>30 Hz) does not. In this paper, a mobile robot is remotely navigated into an office environment by means of an asynchronous high-frequency SSVEP-based BCI along with the image of a video camera. This BCI uses only three electroencephalographic channels and a simple processing signal method. The robot velocity control and the avoidance obstacle algorithms are also herein described. Seven volunteers were able to drive the mobile robot towards two different places. They had to evade desks and shelves, pass through a doorway and navigate in a corridor. The system was designed so as to allow the subject to move about without restrictions, since he/she had full robot movement's control. It was concluded that the developed system allows for remote mobile robot navigation in real indoor environments using brain signals. The proposed system is easy to use and does not require any special training. The user's visual fatigue is reduced because high-frequency stimulation is employed and, furthermore, the user gazes at the stimulus only when a command must be sent to the robot.

A Neurally Controlled Computer Game Avatar With Humanlike Behavior

This paper describes the NeuroBot system, which uses a global workspace architecture, implemented in spiking neurons, to control an avatar within the Unreal Tournament 2004 (UT2004) computer game. This system is designed to display humanlike behavior within UT2004, which provides a good environment for comparing human and embodied AI behavior without the cost and difficulty of full humanoid robots. Using a biologically inspired approach, the architecture is loosely based on theories about the high-level control circuits in the brain, and it is the first neural implementation of a global workspace that has been embodied in a complex dynamic real-time environment. NeuroBot's humanlike behavior was tested by competing in the 2011 BotPrize competition, in which human judges play UT2004 and rate the humanness of other avatars that are controlled by a human or a bot. NeuroBot came a close second, achieving a humanness rating of 36%, while the most human human reached 67%. We also developed a humanness metric that combines a number of statistical measures of an avatar's behavior into a single number. In our experiments with this metric, NeuroBot was rated as 33% human, and the most human human achieved 73%.

Linear Parameter-Varying Modeling for Gain-Scheduling Robust Control Synthesis of Flexible Joint Industrial Robot

Industrial robot features a multivariable, nonlinear and coupled dynamics property, which is always the inevitable topic for control engineer to face during the design of motion controller to achieve desired performance. In the past half century, motion control of industrial robot has gone through a sustainable development from no model involved to model based, from rigid body model to flexible joint model, and even more delicate models of higher order with flexibility in non-drive-train components are also introduced lately. Involvement of gradually refined dynamic model into control design, as well as manipulator design, has become a dominating approach for robot manufacturer to pursue competitive performance and keep technological leadership. Focusing on dynamic modeling, this paper introduces the formulation and approximation of a novel linear parameter-varying (LPV) model for the three main axes of typical six degrees-of-freedom (DOF) elbow type robot, which converts the strong nonlinear system into a quasi linear one globally dependent on certain scheduling parameters. This modeling method, as the prerequisite step for gain-scheduling robust control synthesis, paves the way for further step towards the implementation of LPV gain-scheduling modeling and control techniques for full robot in the next step.

Proportional–derivative impedance control of robot manipulators for interaction tasks

This paper addresses the problem of impedance control of robot manipulators. An impedance controller with dynamic compensation, applied to the interaction control of robot manipulators, is presented. Previous results on motion control in task-space are extended to generate the proposed impedance controller. The approach was designed in such a way that it solves two challenges: the regulation of the interaction and a suitable path tracking. The asymptotic stability of the closed-loop system, composed by full non-linear robot dynamics and the impedance controller, is demonstrated in agreement with Lyapunov’s direct method. In addition to the theoretical background, the performance of the proposed controller is verified through simulation and experimental results obtained from the implementation of an interaction task involving a two degree-of-freedom, direct-drive robot.

New 3-DOFs Hybrid Mechanism for Ankle and Wrist of Humanoid Robot: Modeling, Simulation, and Experiments

This paper deals with the design of a new class of hybrid mechanism dedicated to humanoid robotics application. Since the designing and control of humanoid robots are still open questions, we propose the use of a new class of mechanisms in order to face several challenges that are mainly the compactness and the high power to mass ratio. Human ankle and wrist joints can be considered more compact with the highest power capacity and the lowest weight. The very important role played by these joints during locomotion or manipulation tasks makes their design and control essential to achieve a robust full size humanoid robot. The analysis of all existing humanoid robots shows that classical solutions (serial or parallel) leading to bulky and heavy structures are usually used. To face these drawbacks and get a slender humanoid robot, a novel three degrees of freedom hybrid mechanism achieved with serial and parallel substructures with a minimal number of moving parts is proposed. This hybrid mechanism that is able to achieve pitch, yaw, and roll movements can be actuated either hydraulically or electrically. For the parallel submechanism, the power transmission is achieved, thanks to cables, which allow the alignment of actuators along the shin or the forearm main axes. Hence, the proposed solution fulfills the requirements induced by both geometrical, power transmission, and biomechanics (range of motion) constraints. All stages including kinematic modeling, mechanical design, and experimentation using the HYDROïD humanoid robot’s ankle mechanism are given in order to demonstrate the novelty and the efficiency of the proposed solution.

Cast floor robotics: concept and latest test results

SIEMENS-VAI started the development for full automatic operation of all activities on the cast floor of continuous casting machines. A full size test robot was installed in a laboratory with on board position detection and all necessary tools. Specific solutions for allowing full automatic operation were engineered, manufactured and tested. The first robot will go in operation in December 2007.

USARSim: Simulation for the Study of Human-Robot Interaction

The PackBots being used by the U.S. military in Afghanistan and the urban search and rescue (USAR) robots that worked the World Trade Center site are just two recent examples of mobile robots moving from the laboratory to the field. What is significant about these new applications is that they invariably involve some form of human-robot interaction (HRI) rather than the full robot autonomy that has motivated most prior research. Conducting HRI research can be extremely difficult because experimentation with physical robots is expensive and time consuming. Few roboticists have experience or interest in conducting human experimentation, and researchers in human factors or human-computer interaction often lack experience in programming robots or access to robotic platforms. In this paper, we describe a high-fidelity, open-source simulation intended for HRI researchers of varying backgrounds and provide reference tasks and environments to facilitate collaboration in order to share the results. The architecture and capabilities of the game engine–based USARSim simulation are described. Its use for HRI research is illustrated through case studies describing experiments in camera control for remote viewing and integrated display of attitude information.

A new variable structure PID-controller design for robot manipulators

In this brief, a new variable structure proportional-integral-derivative (PID) controller design approach is considered for the tracking stabilization of robot motion. The work corroborates the utility of a certain PID sliding mode controller with PID sliding surface for tracking control of a robotic manipulator. Different from the general approach, the conventional equivalent control term is not used in this controller because that needs to use the matching conditions and exact full robot dynamics knowledge, which involves unavailable parameter uncertainties. Though the sliding surface includes also the integral error term, which makes the robot tracking control problem complicated, the existence of a sliding mode and gain selection guideline are clearly investigated. Moreover, different from uniformly ultimately boundedness, the global asymptotic stability of the robot system with proposed controller is analyzed. The sliding and global stability conditions are formulated in terms of Lyapunov full quadratic form and upper and lower matrix norm inequalities. Reduced design is also discussed. The proposed control algorithm is applied to a two-link direct drive robot arm through simulations. The simulation results indicate that the control performance of the robot system is satisfactory. The chattering phenomenon is handled by the use of a saturation function replaced with a pure signum function in the control law. The saturation function results in a smooth transient performance. The proposed approach is compared with the existing alternative sliding mode controllers for robot manipulators in terms of advantages and control performances. A comparative analysis with a plenty of simulation results soundly confirmed that the performance of developed variable structure PID controller is better under than those of both classical PID controller and an existing variable structure controller with PID-sliding surface.

The Multi‐frequency Robotic facility REM: first results

AbstractThe REM Observatory, recently installed and commissioned at la Silla Observatory Chile, is the first moderate aperture robotic telescope able to cover simultaneously the visible‐NIR (0.45‐2.3 microns) wavelength range. Due to its very fast pointing and its full robotization REM is conceived for fast transients observation. The high throughput Infrared Camera (REMIR) and the Visible imaging spectrograph (ROSS), simultaneously fed by a dichroic, allow to collect high S/N data in an unprecedented large spectral range on a telescope of this size. The REMobservatory is an example of a versatile and agile facility necessary complement to large telescopes in fields in which rapid response and/or target pre‐screening are necessary. This paper describes the principal Characteristics and operation modes of the REM observatory and gives on overview of the preliminary results obtained during the commissioning phase. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

完全自立型ヒューマノイドロボットiHs04の開発(ヒューマノイド1)

完全自立型ヒューマノイドロボットiHs04の開発(ヒューマノイド1)

Predictive reference shaping for constrained robotic systems using evolutionary algorithms

This paper proposes a method for reducing the trajectory tracking errors of robotic systems in presence of input saturation and state constraints. Basing on a finite horizon prediction of the future evolution of the robot dynamics, the proposed device online preshapes the reference trajectory, minimizing a multi-objective cost function. The shaped reference is updated at discrete time intervals and is generated taking into account the full nonlinear robot dynamics, input and state constraints. A specialized Evolutionary Algorithm is employed as search tool for the online computation of a sub-optimal reference trajectory in the discretized space of the control alternatives. The effectiveness of the proposed method and the online computational burden are analyzed numerically in two significant robotic control problems; furthermore a comparison of the performance provided by this method and an iterative gradient-based algorithms are discussed.

Transforming a surgical robot for human telesurgery

This paper discusses the technology and developments behind transformations made to a commercial robotic surgical system, Computer Motion, Inc.'s Zeus/spl trade/, in order to make it possible to fully and safely support minimally-invasive human telesurgery performed over very large distances. Because human life is at stake, issues relating to safety, detection of errors, and fail-safe operation are principal in importance. Therefore, it was paramount that all of the safety features of the commercial product Zeus/spl trade/ remained intact during this transformation. This paper discusses the commercial robot and its safety features as well as the real-time communications system added to it as part of Operation Lindbergh, the first transatlantic human telesurgery. Particular attention is paid to the limiting effects of latency. Key techniques developed during this project are discussed, including the need to send the full robot state in each transmitted packet rather than incremental or modal data, thereby treating all telecom problems uniformly as dropped packets. The use of hierarchical design (incorporating Zeus as a drop-in component rather than modifying its internals) allowed the project to focus on the new issues arising due to teleoperation while gaining the robust, error checking, and fail-safe aspects of the design from the use of the unmodified commercial robot. The concept of local mode was created and used during initialization and during communications abnormalities and outages in order to keep the local and remote subsystems active and safely quiescent.

Adaptive servo visual robot control

Adaptive controllers for robot positioning and tracking using direct visual feedback with camera-in-hand configuration are proposed in this paper. The controllers are designed to compensate for full robot dynamics. Adaptation is introduced to reduce the design sensitivity due to robot and payload dynamics uncertainties. It is proved that the control system achieves the motion control objective in the image coordinate system. Simulations are carried out to evaluate the controller performance. Also, discretization and measurement effects are considered in simulations.

Manipulator path planning by decomposition: algorithm and analysis

Path planning is achieved by a special decomposition of the robot manipulator, an offline preprocessing stage, and a three phase online path planning scheme. The decomposition consists of separating the robot into several chains where a chain is a combination of several consecutive links and joints. Preprocessing is performed by defining a set of postures for each chain and setting up a collision table which re-integrates the chains into the full robot and stores the collision states of various discretized robot configurations with the obstacles. Path planning using a local search is performed independently in joint subspaces associated with robot chains. The paths found for the chains are synthesized to obtain a collision-free path for the robot. This decomposition reduces the exponential growth of computation with robot degrees of freedom (DOF) to that of the much lower chain DOF. As a result, it is possible to achieve short planning times for practical robots operating in three-dimensional work spaces. Analysis of computation time and space of the proposed method are presented. Results supporting the analysis are provided for a large number of path-planning trials with two practical robots operating in relatively cluttered environments.

Tracking adaptive impedance robot control with visual feedback

In this paper we propose a tracking adaptive impedance controller for robots with visual feedback. It is based on a generalized impedance concept where the sensed distance is introduced as a fictitious force to the control in order to avoid obstacles in restricted motion tasks. The controller is designed to compensate for full non-linear robot dynamics. Robot parameters adjustment is introduced to reduce the sensibility of the controller design to dynamic uncertainties of the robot and the manipulated load. It is proved that the vision control errors are ultimately bounded in the image coordinate system. Simulations are carried out to evaluate the controller performance.

Trajectory optimization of industrial robots with application to computer-aided robotics and robot controllers

The workcycle time in automated car manufacturing lines CSLYI be reduced by optinizing the robot trajectories for off-line programming. Thus, improved set points for the on-line robot controller are obtained. In this paper, direct transcription methods are described for solving the constrained trajectory optimization problems by using full dynamic robot models. The optimization methods can be used conveniently in combination with computer-aided robotics (CAR) tools and current robot controllers. This is demonstrated by simulation and experimental results for an ABB IRB 6400 industrial robot

Optimal Robot Motion Planning and Work-Cell Layout Design

This paper describes an interactive software system, developed at the Robotics and Automation Laboratory at UCLA to demonstrate innovative approaches to off-line robot programming and work-cell layout design. The software computes the time-optimal motions along specified paths, local optimal paths around an initial guess, and the global optimal path between given end-points. It considers the full robot dynamics, actuator constraints, on the payload acceleration or the gripping force, and any number of polygonal obstacles of any shape. The graphic displays provide a useful tool for interactive motion planning and workcell design.

Adaptive explicit force control of position-controlled manipulators

This article presents a new adaptive outer-loop approach for explicit force regulation of position-controlled robot manipulators. The strategy is computationally simple and does not require knowledge of the manipulator dynamic model, the inner-loop position controller parameters, or the environment. It is shown that the control strategy guarantees global uniform boundedness of all signals and convergence of the position/force regulation errors to zero when applied to the full nonlinear robot dynamic model. If bounded external disturbances are present, a slight modification to the control scheme ensures that global uniform boundedness of all signals is retained and that arbitrarily accurate stabilization of the regulation errors can be achieved. Additionally, it is shown that the adaptive controller is also applicable to robotic systems with PID inner-loop position controllers. Computer simulation results are given for a Robotics Research Corporation (RRC) Model K-1207 redundant arm and demonstrate that accurate and robust force control is achievable with the proposed controller. Experimental results are presented for the RRC Model K-1207 robot and confirm that the control scheme provides a simple and effective means of obtaining high-performance force control. © 1996 John Wiley & Sons, Inc.

Tracking Adapitive Control of Robots with Visual Feedback

In this paper an adaptive controller for robot tracking using visual feedback with camerain-hand configuration is proposed. The controller is designed to compensate for full robot dynamics. Adaptation is introduced to reduce the design sensitivity due to robot and payload dynamic uncertainties. It is proved that the vision control errors are ultimately bounded in the image coordinate system. Simulations are carried out to evaluate the controller performance.

A neural network based feedforward adaptive controller for robots

In this paper, an adaptive controller for robot manipulators which uses neural networks is presented. The proposed control scheme is based on PD feedback plus a feedforward compensation of full robot dynamics. The feedforward signal is obtained by summing up the weighted outputs of a set of fixed multilayer neural nets. The controller is adaptive to robot dynamics and payload uncertainties. A stability analysis which takes into account neural network learning errors is included. Simulation results showing the feasibility and performance of the approach are given. >