Pose Optimization of Serial Manipulators Using Knowledge of Their Velocity‐Degenerate (Singular) Configurations

This work investigates the exploitation of velocity‐degenerate configurations to optimize the pose of either nonredundant or redundant serial manipulators to sustain desired wrenches. An algorithm is developed that determines a desirable start point for the optimization of a serial manipulator's pose. The start‐point algorithm (SPA) uses analytical expressions of the velocity‐degenerate (singular) configurations of a serial manipulator to determine a pose that would be best suitable to sustain a desired wrench. Results for an example redundant serial manipulator are presented. The example results show that by using the SPA with the optimization routine, the resulting poses obtained require less effort from the actuators when compared to the poses obtained without using the SPA. It is shown that when no constraint is imposed on the position of the end‐effector, the SPA excels at providing a better solution with less iterations than running the optimization without the SPA. © 2003 Wiley Periodicals, Inc.     

Disturbance rejection for space‐based manipulators

Most industrial manipulators operate from a fixed base. Hence, there are no disturbances from the environment to alter the position of the end‐effector. On the other hand, manipulators that are mounted on mobile platforms are subject to disturbances emerging from unwanted motion at the base. Similarly, manipulators that perform delicate operations in space while on board in‐orbit spacecraft experience disturbances. This article describes the design and implementation of a disturbance rejection controller for a 6 degree‐of‐freedom (DOF) programable universal manipulator for assembly (PUMA) manipulator mounted on a 3‐DOF platform. A control algorithm is designed to track the desired position and attitude of the end‐effector in inertial space, subject to unknown disturbances in the platform axes. Experimental results are presented for step, sinusoidal, and random disturbances in the platform rotational axis and in the neighborhood of kinematic singularities. ©1999 John Wiley & Sons, Inc.     

Robot manipulator control for hazardous waste-handling applications

The U.S. Department of Energy has identified robotics as a major technology to be utilized in its program of environmental restoration and waste management, and in particular has targeted robotic handling of hazardous waste to be an essential element in this program. Successful performance of waste-handling operations will require a robot to perform complex tasks involving both accurate positioning of its end effector and compliant contact between the end effector and the environment, and will demand that these tasks be completed in uncertain surroundings. This article focuses on the development of a robot control system capable of meeting the requirements of hazardous-waste-handling applications and presents as a solution an adaptive scheme for controlling the mechanical impedance of kinematically redundant manipulators. The proposed controller is capable of accurate end effector impedance control and effective redundancy utilization, does not require knowledge of the complex robot dynamic model or parameter values for the robot or the environment, and is implemented without calculation of the robot inverse kinematic transformation. Computer simulation results are given for a 4 degree of freedom redundant robot under adaptive impedance control. These results indicate that the proposed controller is capable of successfully performing tasks of importance in robotic waste-handling applications.     

A field‐tested robotic harvesting system for iceberg lettuce

Agriculture provides an unique opportunity for the development of robotic systems; robots must be developed which can operate in harsh conditions and in highly uncertain and unknown environments. One particular challenge is performing manipulation for autonomous robotic harvesting. This paper describes recent and current work to automate the harvesting of iceberg lettuce. Unlike many other produce, iceberg is challenging to harvest as the crop is easily damaged by handling and is very hard to detect visually. A platform called Vegebot has been developed to enable the iterative development and field testing of the solution, which comprises of a vision system, custom end effector and software. To address the harvesting challenges posed by iceberg lettuce a bespoke vision and learning system has been developed which uses two integrated convolutional neural networks to achieve classification and localization. A custom end effector has been developed to allow damage free harvesting. To allow this end effector to achieve repeatable and consistent harvesting, a control method using force feedback allows detection of the ground. The system has been tested in the field, with experimental evidence gained which demonstrates the success of the vision system to localize and classify the lettuce, and the full integrated system to harvest lettuce. This study demonstrates how existing state‐of‐the art vision approaches can be applied to agricultural robotics, and mechanical systems can be developed which leverage the environmental constraints imposed in such environments.     

On singular behaviors of impedance‐based repeatable control for redundant robots

This article addresses the association between the unstiffening phenomena in structural mechanics and the algorithmic singularities encountered in the impedance‐based repeatable control algorithms used to command redundant manipulators. It is well known that velocity control schemes such as the pseudoinverse control schemes do not guarantee repeatability for redundant manipulators. In other words, for a closed end‐effector trajectory, the joints do not, in general, exhibit a closed trajectory. One way to overcome this problem is to model each joint with compliance and incorporate a second‐order correction term for the pseudoinverse. With this model, the joint configuration adopted by the manipulator at a given point in task space is one which minimizes the artificial potential energy of the system and is locally unique. In terms of statics, this is equivalent to saying that the elastic structure reaches its static equilibrium under external load. Keep this analogy in mind. We know that the impedance control commands the manipulator to mimic the behavior of an elastic articulated chain. For any phenomena observable on a real elastic structure, we should be able to find its counterpart embedded in the impedance control. In this article, we analyze the performance of such repeatable control algorithms from the point of view of structure mechanics. Singularities in the algorithm are examined and their significance in mechanics are also discussed. © 2001 John Wiley & Sons, Inc.     

Auditory driven subband speech enhancement for automatic recognition of noisy speech

Speech recognizers achieve high recognition accuracy under quiet acoustic environments, but their performance degrades drastically when they are deployed in real environments, where the speech is degraded by additive ambient noise. This paper advocates a two phase approach for robust speech recognition in such environment. Firstly, a front end subband speech enhancement with adaptive noise estimation (ANE) approach is used to filter the noisy speech. The whole noisy speech spectrum is portioned into eighteen dissimilar subbands based on Bark scale and noise power from each subband is estimated by the ANE approach, which does not require the speech pause detection. Secondly, the filtered speech spectrum is processed by the non parametric frequency domain algorithm based on human perception along with the back end building a robust classifier to recognize the utterance. A suite of experiments is conducted to evaluate the performance of the speech recognizer in a variety of real environments, with and without the use of a front end speech enhancement stage. Recognition accuracy is evaluated at the word level, and at a wide range of signal to noise ratios for real world noises. Experimental evaluations show that the proposed algorithm attains good recognition performance when signal to noise ratio is lower than 5 dB.     

A guidance‐based motion‐planning methodology for the docking of autonomous vehicles

In this paper, a generic line‐of‐sight‐sensing (LOS)‐based guidance methodology is proposed for the docking of autonomous vehicles/robotic end‐effectors: A multi‐LOS task‐space sensing system is used in conjunction with a guidance algorithm in a closed‐loop feedback environment. The novelty of the overall system is its applicability to cases that do not allow for the direct proximity measurement of the vehicle's pose (position and orientation). In such instances, a guidance‐based technique must be employed to move the vehicle to its desired pose using corrective actions at the final stages of its motion. Namely, after the vehicle/end‐effector has failed to move to its desired docking pose within acceptable tolerances, LOS sensors initiate short‐range corrective motion commands. The objective of the proposed guidance method is, thus, to successfully minimize the systematic errors of the vehicle, accumulated after a long‐range motion, while allowing it to converge within the random noise limits. An additional advantage of the proposed system is its applicability to varying vehicle mobility requirements for high‐precision docking. The proposed system was successfully tested via simulation on a 6 degree‐of‐freedom (DOF) vehicle. Numerous simulation tests of the behavior of the vehicle under the command of the guidance algorithm were conducted, one of which is presented herein. © 2005 Wiley Periodicals, Inc.     

Rough terrain mapping and classification for foothold selection in a walking robot

Although legged locomotion over a moderately rugged terrain can be accomplished by employing simple reactions to the ground contact information, a more effective approach, which allows predictively avoiding obstacles, requires a model of the environment and a control algorithm that takes this model into account when planning footsteps and leg movements. This article addresses the issues of terrain perception and modeling and foothold selection in a walking robot. An integrated system is presented that allows a legged robot to traverse previously unseen, uneven terrain using only onboard perception, provided that a reasonable general path is known. An efficient method for real‐time building of a local elevation map from sparse two‐dimensional (2D) range measurements of a miniature 2D laser scanner is described. The terrain mapping module supports a foothold selection algorithm, which employs unsupervised learning to create an adaptive decision surface. The robot can learn from realistic simulations; therefore no a priori expert‐given rules or parameters are used. The usefulness of our approach is demonstrated in experiments with the six‐legged robot Messor. We discuss the lessons learned in field tests and the modifications to our system that turned out to be essential for successful operation under real‐world conditions. © 2011 Wiley Periodicals, Inc.     

基于双多线激光雷达的非结构化环境负障碍感知技术

负障碍感知是非结构化环境下的难点问题,本文针对该问题提出一种新的基于双多线激光雷达（Light detection and ranging,LiDAR）的感知方法.采用分布嵌入式架构对双激光雷达数据进行同步采集与实时处理,将雷达点云映射到多尺度栅格,统计栅格的点云密度与相对高度等特征并标记,从点云数据提取负障碍几何特征,通过将栅格的统计特征与负障碍的几何特征做多特征关联找到关键特征点对,将特征点对聚类并过滤,识别出负障碍.方法不受地面平整度影响,已成功应用在无人驾驶车上.使用表明该方法具有较高的实时性和可靠性,在非结构化环境下具有良好的感知效果.     

Reflectance based object recognition

Neighboring points on a smoothly curved surface have similar surface normals and illumination conditions. Therefore, their brightness values can be used to compute the ratio of their reflectance coefficients. Based on this observation, we develop an algorithm that estimates a reflectance ratio for each region in an image with respect to its background. The algorithm is efficient as it computes ratios for all image regions in just two raster scans. The region reflectance ratio represents a physical property that is invariant to illumination and imaging parameters. Several experiments are conducted to demonstrate the accuracy and robustness of ratio invariant.The ratio invariant is used to recognize objects from a single brightness image of a scene. Object models are automatically acquired and represented using a hash table. Recognition and pose estimation algorithms are presented that use ratio estimates of scene regions as well as their geometric properties to index the hash table. The result is a hypothesis for the existence of an object in the image. This hypothesis is verified using the ratios and locations of other regions in the scene. This approach to recognition is effective for objects with printed characters and pictures. Recognition experiments are conducted on images with illumination variations, occlusions, and shadows. The paper is concluded with a discussion on the simultaneous use of reflectance and geometry for visual perception.     

Synthesis of slow‐wave structures based on capacitive‐loaded lines through aggressive space mapping (ASM)

This article is focused on the automated synthesis of slow‐wave structures based on microstrip lines loaded with patch capacitors. Thanks to the presence of the shunt capacitors, the effective capacitance of the line is enhanced, and the phase velocity of the structure can be made significantly smaller than the one of the unloaded line. The target is to achieve the layout of the slow‐wave structure able to provide the required slow‐wave ratio, characteristic (Bloch) impedance and electrical length (i.e., the usual specifications in the design of slow‐wave transmission lines). To this end, a two‐step synthesis method, based on the aggressive space mapping (ASM) algorithm, is proposed for the first time. Through the first ASM algorithm, the circuit schematic providing the target specifications is determined. Then, the second ASM optimizer is used to generate the layout of the structure. To illustrate the potential of the proposed synthesis method, three application examples are successfully reported. The two‐step ASM algorithm is able to provide the layout of the considered structures from the required specifications, without the need of an external aid in the process. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:629–638, 2015.     

Gradient‐based steering for vision‐based crowd simulation algorithms

Most recent crowd simulation algorithms equip agents with a synthetic vision component for steering. They offer promising perspectives through a more realistic simulation of the way humans navigate according to their perception of the surrounding environment. In this paper, we propose a new perception/motion loop to steering agents along collision free trajectories that significantly improves the quality of vision‐based crowd simulators. In contrast with solutions where agents avoid collisions in a purely reactive (binary) way, we suggest exploring the full range of possible adaptations and retaining the locally optimal one. To this end, we introduce a cost function, based on perceptual variables, which estimates an agent's situation considering both the risks of future collision and a desired destination. We then compute the partial derivatives of that function with respect to all possible motion adaptations. The agent then adapts its motion by following the gradient. This paper has thus two main contributions: the definition of a general purpose control scheme for steering synthetic vision‐based agents; and the proposition of cost functions for evaluating the perceived danger of the current situation. We demonstrate improvements in several cases.     

Introducing Radius of Torsure and Cylindroid of Torsure

Robotic path planning can involve the specification of the position and orientation of an end‐effector to achieve a desired task (e.g., deburring, welding, or surface metrology). Under such scenarios the end‐effector is instantaneously rotating and translating about a unique axis; the ISA. Alternately, the performance of direct contact mechanisms (viz., cam systems and gear pairs) are dependent on the surface geometry between two surfaces in direct contact. Determination of this geometry can entail the parametrization of a family of geodesics curves embedded within each surface. This parametrization is tantamount to an end‐effector rotating and translating about an ISA. In both scenarios there is a unique ISA for each geodesic embedded in a surface. Here, curvature and torsion of a spatial curve are coupled together to define an alternative definition for the radius‐of‐curvature of a spatial curve. This new definition is identified as radius of torsure to distinguish it from the classical definition for radius‐of‐curvature. Further, it is shown that the family of twists that corresponds to the pencil of geodesics coincident with a point on a surface defines a cylindroid: the cylindroid of torsure. An illustrative example is provided to demonstrate this difference. © 2003 Wiley Periodicals, Inc.     

智轨电车多源环境感知系统

智轨电车的多源环境感知系统是车载平台与运行环境的交互纽带,其包括基于激光雷达的障碍物感知子系统、基于毫米波雷达的前侧向障碍物感知子系统以及基于多摄像头的360度环视子系统。基于激光雷达的障碍物感知子系统采用地面分割算法、点云聚类算法和数据关联算法,实现了对运行前方障碍物的检测和跟踪;基于毫米波雷达的前侧向障碍物感知子系统采用目标检测算法和跟踪算法,实现侧向以及前向障碍物探测;基于分布式鱼眼摄像头的360度环视子系统运用图像拼接算法,实现智轨电车周围障碍物感知和预警。实车试验结果表明,该环境感知系统可有效地提高智轨电车的运行安全系数,为车辆智能驾驶提供了全面的环境信息。     

Fuzzy maps: A new tool for mobile robot perception and planning

An essential component of an autonomous mobile robot is the exteroceptive sensory system. Sensing capabilities should be integrated with a method for extracting a representation of the environment from uncertain sensor data and with an appropriate planning algorithm. In this article, fuzzy logic concepts are used to introduce a tool useful for robot perception as well as for planning collision-free motions. In particular, a map of the environment is defined as the fuzzy set of unsafe points, whose membership function quantifies the possibility for each point to belong to an obstacle. The computation of this set is based on a specific sensor model and makes use of intermediate sets generated from range measures and aggregated by means of fuzzy set operators. This general approach is applied to a robot with ultrasonic rangefinders. The resulting map building algorithm performs well, as confirmed by a comparison with stochastic methods. The planning problem on fuzzy maps can be solved by defining various path cost functions, corresponding to different strategies, and by searching the map for optimal paths. To this end, proper instances of the A* algorithm are devised. Experimental results for a Nomad 200™ robot moving in a real-world environment are presented. © 1997 John Wiley & Sons, Inc.     

Long‐range rover localization by matching LIDAR scans to orbital elevation maps

Current rover localization techniques such as visual odometry have proven to be very effective on short‐ to medium‐length traverses (e.g., up to a few kilometers). This paper deals with the problem of long‐range rover localization (e.g., 10 km and up) by developing an algorithm named MOGA (Multi‐frame Odometry‐compensated Global Alignment). This algorithm is designed to globally localize a rover by matching features detected from a three‐dimensional (3D) orbital elevation map to features from rover‐based, 3D LIDAR scans. The accuracy and efficiency of MOGA are enhanced with visual odometry and inclinometer/sun‐sensor orientation measurements. The methodology was tested with real data, including 37 LIDAR scans of terrain from a Mars–Moon analog site on Devon Island, Nunavut. When a scan contained a sufficient number of good topographic features, localization produced position errors of no more than 100 m, of which most were less than 50 m and some even as low as a few meters. Results were compared to and shown to outperform VIPER, a competing global localization algorithm that was given the same initial conditions as MOGA. On a 10‐km traverse, MOGA's localization estimates were shown to significantly outperform visual odometry estimates. This paper shows how the developed algorithm can be used to accurately and autonomously localize a rover over long‐range traverses. © 2010 Wiley Periodicals, Inc.     

An improved trajectory planner for redundant manipulators in constrained workspace

This article studies the trajectory planning of redundant robots performing tasks within an enclosed workspace. Configuration control of kinematically redundant manipulators using the pseudo‐inverse with null‐space projection method is a well‐known scheme. One advantage of this method is that the gradient of an objective function can be included in the homogeneous term to optimize the objective function without affecting the position of the end‐effector. Using different objective functions, this method can achieve redundancy resolution such as obstacle or joint limits avoidance. Along this line of redundancy resolution, a switching objective function is proposed. We modify Liegeois' joint angle availability objective function so that the midpoints of each joint are switched at a series of prespecified key path points for the end‐effector to achieve. These key path points are planned beforehand according to the geometry of the constrained workspace. The trajectory planning problem can then be viewed as a series of proper postures (i.e., midpoints) determination problems at the key path points. The proper postures are determined using a combination of the potential field method and the elastic model method that takes into account joint operating ranges and the motion tendency of the end‐effector. A variable weighting technique to achieve the proper postures effectively is also presented. Simulations of a planar eight‐link robot in a constrained workspace illustrate the effectiveness of the switching objective function with the variable weighting approach in trajectory planning problems. ©1999 John Wiley & Sons, Inc.     

Planar Translational Cable‐Direct‐Driven Robots

We present the simulated dynamics and control of a planar, translational cable‐directdriven robot (CDDR). The motivation behind this work is to improve the serious cable interference problem with existing CDDRs and to avoid configurations where negative cable tensions are required to exert general forces and moments on the environment and during dynamic motions. Generally for CDDRs the commanded rotations are more demanding than commanded translations in terms of slack cable conditions. Therefore we propose a translational CDDR whose end‐effector may be fitted with a traditional serial wrist mechanism to provide rotational freedom (assuming proper design to resist the moments). Only the translational CDDR is considered in this article, including kinematics and statics modeling, statics workspace (wherein all possible Cartesian forces and moments may be exerted with only positive cable tensions), plus a dynamics model and simulated control for planar CDDRs. Here we focus only on planar CDDRs, to clearly demonstrate our dynamics and control work; we will extend this work to spatial CDDRs in the future. Examples are presented to demonstrate simulated control including feedback linearization of the four‐cable CDDR (with one degree of actuation redundancy) performing a Cartesian task. An on‐line dynamic minimum torque estimation algorithm is introduced to ensure all cable tensions remain positive for all motion; otherwise slack cables can result from CDDR dynamics and control is lost. © 2003 Wiley Periodicals, Inc.     

Establishment of overall workload assessment technique for various tasks and workplaces

A model for assessing workloads called overall workload level (OWL) was developed by introducing linguistic variable sets and applying the analytic hierarchy process (AHP) to estimate the external workload imposed on a human operator in man–machine systems. To do this, a five-point linguistic variable set scale was constructed and their hierarchical prioritization procedures were set up. The task and workplace variables (e.g., physical, environmental, postural, and mental job demand workloads) which can obtain the operator's perception of workload are selected as workload factors and the AHP technique is used to collect different weights. Finally, OWL is calculated using a computer-assisted system to determine the level of overall workload impinged on an operator. The OWL was implemented in an actual industrial environment from a physiological and epidemiological viewpoint to determine the validity of the model. Furthermore, the results obtained by applying OWL were compared to the results obtained by applying the overall workload (OW) of the NASA task load index (TLX). The results show that there is a close linear relationship among the physiological measurements, the severity of injury and illness rates, OW, and OWL. Thus, this approach can be used for problem identification and for solving widespread occupational workloads.

Relevance to industry

The determination of workloads imposed on a human operator plays an important role in designing and evaluating an existing man–machine system. Therefore, a model for assessing workloads was developed to estimate the external workload imposed on a human operator in man–machine systems. This model can be used for problem identification and for solving widespread occupational workload.