Sequencing of multi‑robot behaviors using reinforcement learning

Given a collection of parameterized multi-robot controllers associated with individual behaviors designed for particular tasks, this paper considers the problem of how to sequence and instantiate the behaviors for the purpose of completing a more complex, overarching mission. In addition, uncertainties about the environment or even the mission specifications may require the robots to learn, in a cooperative manner, how best to sequence the behaviors. In this paper, we approach this problem by using reinforcement learning to approximate the solution to the computationally intractable sequencing problem, combined with an online gradient descent approach to selecting the individual behavior parameters, while the transitions among behaviors are triggered automatically when the behaviors have reached a desired performance level relative to a task performance cost. To illustrate the effectiveness of the proposed method, it is implemented on a team of differential-drive robots for solving two different missions, namely, convoy protection and object manipulation.     

Incremental learning of gestures for human–robot interaction

For a robot to cohabit with people, it should be able to learn people’s nonverbal social behavior from experience. In this paper, we propose a novel machine learning method for recognizing gestures used in interaction and communication. Our method enables robots to learn gestures incrementally during human–robot interaction in an unsupervised manner. It allows the user to leave the number and types of gestures undefined prior to the learning. The proposed method (HB-SOINN) is based on a self-organizing incremental neural network and the hidden Markov model. We have added an interactive learning mechanism to HB-SOINN to prevent a single cluster from running into a failure as a result of polysemy of being assigned more than one meaning. For example, a sentence: “Keep on going left slowly” has three meanings such as, “Keep on (1)”, “going left (2)”, “slowly (3)”. We experimentally tested the clustering performance of the proposed method against data obtained from measuring gestures using a motion capture device. The results show that the classification performance of HB-SOINN exceeds that of conventional clustering approaches. In addition, we have found that the interactive learning function improves the learning performance of HB-SOINN.     

Development of “STORK”, a watermelon-harvesting robot

Recently, the production of heavy fruit and vegetables has been decreasing in Japan because strenuous labor is require to harvest them. A robot would allow them to be harvested more easily. We have developed the robot “STORK” to harvest watermelons. STORK has a low mass and a long working range. The position accuracy and repeatability of the manipulator, the required vacuum, and the allowance for position error of the vacuum pad were tested.     

Perception of own and robot engagement in human–robot interactions and their dependence on robotics knowledge

Communication between socially assistive robots and humans might be facilitated by intuitively understandable mechanisms. To investigate the effects of some key nonverbal gestures on a human’s own engagement and robot engagement experienced by humans, participants read a series of instructions to a robot that responded with nods, blinks, changes in gaze direction, or a combination of these. Unbeknown to the participants, the robot had no form of speech processing or gesture recognition, but simply measured speech volume levels, responding with gestures whenever a lull in sound was detected. As measured by visual analogue scales, engagement of participants was not differentially affected by the different responses of the robot. However, their perception of the robot’s engagement in the task, its likability and its understanding of the instructions depended on the gesture presented, with nodding being the most effective response. Participants who self-reported greater robotics knowledge reported higher overall engagement and greater success at developing a relationship with the robot. However, self-reported robotics knowledge did not differentially affect the impact of robot gestures. This suggests that greater familiarity with robotics may help to maximise positive experiences for humans involved in human–robot interactions without affecting the impact of the type of signal sent by the robot.     

The development of an autonomous service robot. Implementation: “Lucas”—The library assistant robot

This paper describes an autonomous mobile device that was designed, developed and implemented as a library assistant robot. A complete autonomous system incorporating human–robot interaction has been developed and implemented within a real world environment. The robotic development is comprehensively described in terms of its localization systems, which incorporates simple image processing techniques fused with odometry and sonar data, which is validated through the use of an extended Kalman filter (EKF). The essential principles required for the development of a successful assistive robot are described and put into demonstration through a human–robot interaction application applied to the library assistant robot.     

Development of the quadruped walking robot,TITAN-IX — mechanical design concept and application for the humanitarian de-mining robot

This paper proposes a quadruped walking robot that has high performance as a working machine. This robot is needed for various tasks controlled by tele-operation, especially for humanitarian mine detection and removal. Since there are numerous personnel landmines that are still in place from many wars, it is desirable to provide a safe and inexpensive tool that civilians can use to remove those mines. The authors have been working on the concept of the humanitarian demining robot systems for 4 years and have performed basic experiments with the first prototype VK-I using the modified quadruped walking robot, TITAN-VIII. After those experiments, it was possible to refine some concepts and now the new robot has a tool (end-effector) changing system on its back, so that by utilizing the legs as manipulation arms and connecting various tools to the foot, it can perform mine detection and removal tasks. Toaccomplish these tasks, we developed various end-effectors that can be attached to the working leg. In this paper we will discuss the mechanical design of the new walking robot called TITAN-IX to be applied to the new system VK-II.     

Human–robot skills transfer interfaces for a flexible surgical robot

In minimally invasive surgery, tools go through narrow openings and manipulate soft organs to perform surgical tasks. There are limitations in current robot-assisted surgical systems due to the rigidity of robot tools. The aim of the STIFF-FLOP European project is to develop a soft robotic arm to perform surgical tasks. The flexibility of the robot allows the surgeon to move within organs to reach remote areas inside the body and perform challenging procedures in laparoscopy. This article addresses the problem of designing learning interfaces enabling the transfer of skills from human demonstration. Robot programming by demonstration encompasses a wide range of learning strategies, from simple mimicking of the demonstrator's actions to the higher level imitation of the underlying intent extracted from the demonstrations. By focusing on this last form, we study the problem of extracting an objective function explaining the demonstrations from an over-specified set of candidate reward functions, and using this information for self-refinement of the skill. In contrast to inverse reinforcement learning strategies that attempt to explain the observations with reward functions defined for the entire task (or a set of pre-defined reward profiles active for different parts of the task), the proposed approach is based on context-dependent reward-weighted learning, where the robot can learn the relevance of candidate objective functions with respect to the current phase of the task or encountered situation. The robot then exploits this information for skills refinement in the policy parameters space. The proposed approach is tested in simulation with a cutting task performed by the STIFF-FLOP flexible robot, using kinesthetic demonstrations from a Barrett WAM manipulator.     

I robot，again

大家一定很奇怪,我为什么要说“又”（again）呢？因为,在很久很久以前（大概是两年以前了吧）,咱们“DF触觉”栏目就为大家带来过一篇名为《I robot》的文章。不过,当时介绍的,都是玩具类的机器人。而这一次,我们要给大家带来的,是几款真正能融入人类生活,真正能为人类提供帮助的机器人。     

Design of a quadruped robot for human–elephant conflict mitigation

Introduction

Human–elephant conflict is a major problem leading to crop damage, human death by elephants and elephants being killed by people. The surveillance and tracking of elephant herds are difficult due to their size and nature of movement.

Materials

In this article, we propose a four-wheeled quadruped robot to mitigate human–elephant conflict. The robot can detect movement of wild pachyderms in certain pockets along the forest borders through which the elephants enter into the human living areas from the forest. The robot is so designed that it can navigate with wheels on flat terrains and with legs on unfriendly rugged terrains with the help of mounted cameras.

Methods

The images of the wild elephant are captured and transmitted to the base stations and an SMS is sent to the forest officials indicating an elephant is found. We obtain a suitable kinematic model for both legs and wheels with control algorithm for the quadruped robot to move along a predetermined path.

Conclusion

The quadruped robot proposed is a solution to detect elephant movement without affecting the ecological conditions to overcome human–elephant conflict. The unpredictability of time and location of elephant arrival into the villages are considered the major issues that are resolved in this work. The results of our work contribute to elephant conservation issues and are suitable for the detection of elephants in forest border areas.     

Improved stability of haptic human–robot interfaces using measurement of human arm stiffness

Necessary physical contact between an operator and a force feedback haptic device creates a coupled system consisting of human and machine. This contact, combined with the natural human tendency to increase arm stiffness to attempt to stabilize its motion, can reduce the stability of the system. This paper proposes a method to increase stability on demand while maintaining speed and performance. Operator arm stiffness is not directly measurable, so controllers cannot typically account for this issue. The causes of arm end-point stiffness are examined as related to system stability, and a method for estimating changes in arm stiffness based on arm muscle activity was designed to provide a robotic controller with additional information about the operator. This was accomplished using electromyograms (EMGs) to measure muscle activities and estimating the level of arm stiffness, which was used to adjust the dynamic characteristics of an impedance controller. To support this design, the correlation between EMGs and arm stiffness was validated experimentally. Further experiments characterized the effects of the designed system on operator performance. This showed increased stability and faster, more accurate movements using the compensating system. Such a system could be used in many applications, including force assisting devices in industrial facilities.     

Shape recognition of laser beam trace for human–robot interface

A robot navigation system using the pattern recognition of figures drawn by a laser pointer has been proposed. Typical figures are registered and assigned to individual robot commands. Each figure is identified based on the feature of its edges. This system detects trace of laser beam and calculates its optical flow vectors. Each figure has its own characteristic distribution pattern of vector inclinations. By evaluating the optical flow pattern of displayed laser spot, the system distinguishes the shape of a laser beam trace and provides the command to a robot corresponding to the drawn figure. The proposed system has been applied to the mobile robot, and shows its effectiveness by steering successfully.     

The Design and Simulation of the 2-D micro-carving parallel robot

introductionR ecent years have witnessed the m icrom ation andintellectualized trend in the study of precise m echanism ,evidenced by the wide exploitation of m ini -robot.Sm all in size, larger in working dom ain, sophisticated indynam ically driving,precise in locating, the m ini-robot,boasts m uch to dealw ith operations in relation with m i-ni-object. M ini-robot goes into 2 m ain categories: spa-tialparallel m echanism (SPM ) and plane parallel m echa-nism (PPM ).Spatialparallel m echan…     

Markerless human–robot interface for dual robot manipulators using Kinect sensor

Remote teleoperation of robot manipulators is often necessary in unstructured, dynamic, and dangerous environments. However, the existing mechanical and other contacting interfaces require unnatural, or hinder natural, human motions. At present, the contacting interfaces used in teleoperation for multiple robot manipulators often require multiple operators. Previous vision-based approaches have only been used in the remote teleoperation for one robot manipulator as well as require the special quantity of illumination and visual angle that limit the field of application. This paper presents a noncontacting Kinect-based method that allows a human operator to communicate his motions to the dual robot manipulators by performing double hand–arm movements that would naturally carry out an object manipulation task. This paper also proposes an innovative algorithm of over damping to solve the problem of error extracting and dithering due to the noncontact measure. By making full use of the human hand–arm motion, the operator would feel immersive. This human–robot interface allows the flexible implementation of the object manipulation task done in collaboration by dual robots through the double hand–arm motion by one operator.     

System identification and control of the ground operationmode of a hybrid aerial–ground robot

This paper presents an in-depth analytical and empirical assessment of the performance of DoubleBee, a novel hybrid aerial– ground robot. Particularly, the dynamic model of the robot with ground contact is analyzed, and the unknown parameters in the model are identified. We apply an unscented Kalman filter-based approach and a least square-based approach to estimate the parameters with given measurements and inputs at every time step. Real data are collected and used to estimate the parameters; test data verify that the values obtained are able to model the rotation of the robot accurately. A gain-scheduled feedback controller is proposed, which leverages the identified model to generate accurate control inputs to drive the system to the desired states. The system is proven to track a constant-velocity reference signal with bounded error. Simulations and real-world experiments using the proposed controller show improved performance than the PID-based controller in tracking step commands and maintaining attitude under robot movement.     

The power manipulability – A new homogeneous performance index of robot manipulators

Jacobian-based performance indices such as the manipulability ellipsoid, the condition number and the minimum singular value, have been very helpful tools both for mechanical manipulator design and for determining suitable manipulator postures to execute a given task. For a manipulator having complex degrees of freedom (translations and rotations), Jacobian matrix becomes non-homogeneous, i.e. it contains elements with different physical units; therefore, the evaluation of its determinant, eigenvalues or singular values needs the combination of quantities of different nature, which is physically inconsistent and moreover it corresponds to a noncommensurable system. In this paper, a new performance index of robot manipulators is proposed. It is fully homogeneous and it constitutes a physically consistent system whether the manipulator contains joints of different natures, or the task space combines both translation and rotation motion. The development is concerned with the study of power within the mechanism. Given that the power has the same physical units in translation and rotation, it can be used as a homogeneous or natural performance index of manipulators by examining the behaviour of its basic components namely, force and speed, at different kinematics configurations. Furthermore, the new concept of vectorial power is introduced, followed by to the quadrivector of apparent power, and leading to the final homogeneous performance index of the power manipulability (PM). This new approach matches perfectly with mechanisms having joints of different natures, as well as with a task space combining both translation and rotation.     

Tracking control of a two-wheeled mobile robot using input–output linearization

This paper discusses the tracking control of two-wheeled mobile robots that have more outputs than inputs. If the number of inputs and the number of outputs are not the same, the inverse of the decoupling matrix in the input–output linearization does not exist. Therefore, a modified input–output linearization method is proposed, to solve the problem by means of a generalized inverse that provides a least-squares solution. The experimental results show that the tracking of posture, position and orientation (the 3-output case) has advantages over position tracking (the 2-output case) from the viewpoint of input power efficiency, because smoother responses can be obtained by considering the orientation.     

Adaptive creeping locomotion of a CPG-controlled snake-like robot to environment change

In this paper, we present a biomimetic approach which is based on Central Pattern Generator (CPG) to solve the difficulty in control of a snake-like robot with a large number of degrees of freedom. A new network with a feedback connection is proposed, which can generate uniform outputs without any additional adjustment. The relations between the CPG parameters and the characteristics of output are also investigated. A simulation platform is also established for the analysis of the CPG-based locomotion control of a snake-like robot. To figure out adaptive creeping locomotion of the robot to the environment with changed friction or the given slope, the relations of CPG parameters and locomotion efficiency by the proposed curvature adaptive principle have been discussed.     

User—robot personality matching and assistive robot behavior adaptation for post-stroke rehabilitation therapy

This paper describes a hands-off socially assistive therapist robot designed to monitor, assist, encourage, and socially interact with post-stroke users engaged in rehabilitation exercises. We investigate the role of the robot’s personality in the hands-off therapy process, focusing on the relationship between the level of extroversion–introversion of the robot and the user. We also demonstrate a behavior adaptation system capable of adjusting its social interaction parameters (e.g., interaction distances/proxemics, speed, and vocal content) toward customized post-stroke rehabilitation therapy based on the user’s personality traits and task performance. Three validation experiment sets are described. The first maps the user’s extroversion–introversion personality dimension to a spectrum of robot therapy styles that range from challenging to nurturing. The second and the third experiments adjust the personality matching dynamically to adapt the robot’s therapy styles based on user personality and performance. The reported results provide first evidence for user preference for personality matching in the assistive domain and demonstrate how the socially assistive robot’s autonomous behavior adaptation to the user’s personality can result in improved human task performance. This work was supported by USC Women in Science and Engineering (WiSE) Program and the Okawa Foundation.     

Simultaneous design of optimal gait pattern and controller for a bipedal robot

Nowadays, biped robotics becomes an interesting topic for many control researchers. The biped robot is more adaptable than the other mobile robots in a varied environment and can have more diverse possibilities in planning the motion. However, it falls down easily and its control for stable walking is difficult. Therefore, generation of a desired walking pattern for the biped robot in the presence of some model uncertainties is an important problem. The proposed walking pattern should be also achievable by the designed controller. To achieve this aim and to reach the best control performance, the walking pattern and controller should be designed simultaneously rather than separately. In the present study, an optimal walking pattern is proposed to be tracked by a designed sliding mode controller. In this respect, a genetic algorithm (GA) is utilized to determine the walking pattern parameters and controller coefficients simultaneously. Here, high stability, minimum energy consumption, good mobility properties, and actuator limitations are considered as the important indexes in optimization. Simulation results indicate the efficiency of the proposed scheme in walking the understudy biped robot.