A biomimetic approach to inverse kinematics for a redundant robot arm

Redundant robots have received increased attention during the last decades, since they provide solutions to problems investigated for years in the robotic community, e.g. task-space tracking, obstacle avoidance etc. However, robot redundancy may arise problems of kinematic control, since robot joint motion is not uniquely determined. In this paper, a biomimetic approach is proposed for solving the problem of redundancy resolution. First, the kinematics of the human upper limb while performing random arm motion are investigated and modeled. The dependencies among the human joint angles are described using a Bayesian network. Then, an objective function, built using this model, is used in a closed-loop inverse kinematic algorithm for a redundant robot arm. Using this algorithm, the robot arm end-effector can be positioned in the three dimensional (3D) space using human-like joint configurations. Through real experiments using an anthropomorphic robot arm, it is proved that the proposed algorithm is computationally fast, while it results to human-like configurations compared to previously proposed inverse kinematics algorithms. The latter makes the proposed algorithm a strong candidate for applications where anthropomorphism is required, e.g. in humanoids or generally in cases where robotic arms interact with humans.     

A dynamics formulation of general constrained robots

The complexity of a standard compact-in-form Lagrangian dynamical expression is proportional to the fourth power of the number of degrees of freedom (DOF) of a robotic system. This fact challenges both simulation and control of robots with hyper degrees of freedom. In this paper, a systematic approach for deriving the dynamical expression of so-called general constrained robots is proposed. This proposed approach has two main features. First, it uses the subsystem dynamics such as the dynamics of joints and rigid links to construct the dynamical expression of the entire robotic system in a closed form. The complexity of the resulted dynamic expression is linearly proportional to the number of DOF of a robotic system. Second, it extends the standard dynamical form and properties of the conventional single-arm constrained robots to a class of more general robotic systems including the coordinated multiple-arm robotic systems. Three spaces, namely the general joint space, the general task space, and the extended subsystems space, are connected through corresponding velocity/force mapping matrices.An erratum to this article can be found at     

在人机协作中基于动量观测和优化算法的全机械臂单点接触信息实时估计

针对协作型机器人,提出了一种依据机器人控制与运动状态信息,基于动量观测与优化算法相结合的全机械臂单点接触信息实时估计方法.该方法将接触位置估计问题转化为优化算法有界搜索问题,搜索范围由动量观测方法确定的接触臂长度确定,两种方法的结合保证了估计的精度和实时性.基于UR机械臂实验平台的仿真与实验结果表明,本文方法能够实时、准确地估计除第1关节以外首次发生接触的机械臂任意位置处的力和位置信息.本研究可以在不借助传感器的情况下实现机械臂对外力的感知.     

A polynomial algorithm for multi-robot 2-cyclic scheduling in a no-wait robotic cell

This paper addresses the multi-robot 2-cyclic scheduling problem in a no-wait robotic cell where exactly two parts enter and leave the cell during each cycle and multiple robots on a single track are responsible for transporting parts between machines. We develop a polynomial algorithm to find the minimum number of robots for all feasible cycle times. Consequently, the optimal cycle time for any given number of robots can be obtained with the algorithm. The proposed algorithm can be implemented in O(N⁷) time, where N is the number of machines in the considered robotic cell.     

A PSO-based algorithm designed for a swarm of mobile robots

This paper presents an algorithm called augmented Lagrangian particle swarm optimization with velocity limits (VL-ALPSO). It uses a particle swarm optimization (PSO) based algorithm to optimize the motion planning for swarm mobile robots. Considering problems with engineering constraints and obstacles in the environment, the algorithm combines the method of augmented Lagrangian multipliers and strategies of velocity limits and virtual detectors so as to ensure enforcement of constraints, obstacle avoidance and mutual avoidance. All the strategies together with basic PSO are corresponding to real situations of swarm mobile robots in coordinated movements. This work also builds a swarm motion model based on Euler forward time integration that involves some mechanical properties such as masses, inertias or external forces to the swarm robotic system. Simulations show that the robots moving in the environment display the desired behavior. Each robot has the ability to do target searching, obstacle avoidance, random wonder, acceleration or deceleration and escape entrapment. So, in summary due to the characteristic features of the VL-ALPSO algorithm, after some engineering adaptation, it can work well for the planning of coordinated movements of swarm robotic systems.     

Robotic clusters: Multi-robot systems as computer clusters: A topological map merging demonstration

In most multi-robot systems, an individual robot is not capable of solving computationally hard problems due to lack of high processing power. This paper introduces the novel concept of robotic clusters to empower these systems in their problem solving. A robotic cluster is a group of individual robots which are able to share their processing resources, therefore, the robots can solve difficult problems by using the processing units of other robots. The concept, requirements, characteristics and architecture of robotic clusters are explained and then the problem of “topological map merging” is considered as a case study to describe the details of the presented idea and to evaluate its functionality. Additionally, a new parallel algorithm for solving this problem is developed. The experimental results proved that the robotic clusters remarkably speedup computations in multi-robot systems. The proposed mechanism can be used in many other robotic applications and has the potential to increase the performance of multi-robot systems especially for solving problems that need high processing resources.     

Planning manipulation movements of a dual-arm system considering obstacle removing

The paper deals with the problem of planning movements of two hand–arm robotic systems, considering the possibility of using the robot hands to remove potential obstacles in order to obtain a free access to grasp a desired object. The approach is based on a variation of a Probabilistic Road Map that does not rule out the samples implying collisions with removable objects but instead classifies them according to the collided obstacle(s), and allows the search of free paths with the indication of which objects must be removed from the work-space to make the path actually valid; we call it Probabilistic Road Map with Obstacles (PRMwO). The proposed system includes a task assignment system that distributes the task among the robots, using for that purpose a precedence graph built from the results of the PRMwO. The approach has been implemented for a real dual-arm robotic system, and some simulated and real running examples are presented in the paper.     

CAMPOUT: a control architecture for tightly coupled coordination of multirobot systems for planetary surface exploration

Exploration of high risk terrain areas such as cliff faces and site construction operations by autonomous robotic systems on Mars requires a control architecture that is able to autonomously adapt to uncertainties in knowledge of the environment. We report on the development of a software/hardware framework for cooperating multiple robots performing such tightly coordinated tasks. This work builds on our earlier research into autonomous planetary rovers and robot arms. Here, we seek to closely coordinate the mobility and manipulation of multiple robots to perform examples of a cliff traverse for science data acquisition, and site construction operations including grasping, hoisting, and transport of extended objects such as large array sensors over natural, unpredictable terrain. In support of this work we have developed an enabling distributed control architecture called control architecture for multirobot planetary outposts (CAMPOUT) wherein integrated multirobot mobility and control mechanisms are derived as group compositions and coordination of more basic behaviors under a task-level multiagent planner. CAMPOUT includes the necessary group behaviors and communication mechanisms for coordinated/cooperative control of heterogeneous robotic platforms. In this paper, we describe CAMPOUT, and its application to ongoing physical experiments with multirobot systems at the Jet Propulsion Laboratory in Pasadena, CA, for exploration of cliff faces and deployment of extended payloads.     

A framework for large‐force task planning of mobile and redundant manipulators

A framework tackling the problem of large wrench application using robotic systems with limited force or torque actuators is presented. It is shown that such systems can apply a wrench to a limited set of Cartesian locations called force workspace (FW), and its force capabilities are improved by employing base mobility and redundancy. An efficient numerical algorithm based on 2ⁿ‐tree decomposition of Cartesian space is designed to generate FW. Based on the FW generation algorithm, a planning method is presented resulting in proper base positioning relative to large‐force quasistatic tasks. Additionally, the case of tasks requiring application of a wrench along a given path is considered. Task workspace, the set of Cartesian space locations that are feasible starting positions for such tasks, is shown to be a subset of FW. This workspace is used for identifying proper base or task positions guaranteeing task execution along desired paths. Finally, to plan redundant manipulator postures during large‐force‐tasks, a new method based on a min–max optimization scheme is developed. Unlike norm‐based methods, this method guarantees no actuator capabilities are exceeded, and force or torque of the most loaded joint is minimized. Illustrative examples are given demonstrating validity and usefulness of the proposed framework. ©1999 John Wiley & Sons, Inc.     

Dynamic process programming for a robotic manipulator based on hopfield NN monotonous optimization searching

A new approach to programming the optimal dynamic process for an n‐joint rigid robotic manipulator with the use of the monotonous optimization searching ability of a Hopfield NN is presented. By combining robotic dynamics, this paper designs a programmed controller, which satisfies the aforementioned dynamic process. The convergence of the programmed controller is investigated. Simulations and experiments demonstrate the effectiveness of the scheme described. © 2004 Wiley Periodicals, Inc.     

Workspace Generation for Multifingered Manipulation

In this paper, we propose a novel numerical approach and algorithm to compute and visualize the workspace of a multifingered hand manipulating an object. Based on feasibility analysis of grasps, the proposed approach uses an optimization technique to first compute discretely the position boundary of the grasped object and then calculate the rotation ranges of the object at specified positions within the boundary. In other words, workspace generation with the approach is fulfilled by obtaining reachable boundaries of the grasped object in the sense of both position and orientation, and the discrete boundary points are computed by a series of optimization models. Unlike in workspace generation of other robotic systems where only geometric and kinematic parameters of the robots are considered, all factors including geometric, kinematic and force-related factors that affect the workspace of a hand–object system can be taken into account in our approach to generate the workspace of multifingered manipulation. Since various constraints can be integrated into the optimization models, our method is general and complete, with adaptability to various grasps and manipulations. Workspace generation with the approach in both planar and spatial cases are illustrated with examples. The approach provides an effective and general solution to the long-term open and challenging problem of workspace generation of multifingered manipulation. Part of the work has been published in the Proceedings of IEEE/RSJ IROS2008 and IEEE/ASME AIM2008.     

An imaginary robot model and double-PD control for redundant robotic systems

The theory and applications of an imaginary robot model with a double-PD control law for redundant robotic systems are presented. The imaginary robot model is based on a special Riemannian metric decomposition for general nonlinear dynamic systems. This model offers an effective way for reducing nonlinear feedback formulation while preserving the linearized system equation. The developed procedure is also applicable to redundant robots. A three-dimensional redundant robot main-frame having three revolute joints plus a prismatic joint is used in the paper to illustrate the design procedure based on the imaginary robot model with the double-PD control scheme. The entire dynamic control algorithm is also verified by a simulation study on the four-joint three-dimensional robot arm.     

Polynomial static output feedback H∞ control via homogeneous Lyapunov functions

In this paper, we study a polynomial static output feedback (SOF) stabilization problem with H_∞ performance via a homogeneous polynomial Lyapunov function (HPLF). It is shown that the quadratic stability ascertaining the existence of a single constant Lyapunov function becomes a special case. With the HPLF, the proposal is based on a relaxed two‐step sum of square (SOS) construction where a stabilizing polynomial state feedback gain K(x) is returned at the first stage and then the obtained K(x) gain is fed back to the second stage, achieving the SOF closed‐loop stabilization of the underlying polynomial fuzzy control systems. The SOS equations obtained thus effectively serve as a sufficient condition for synthesizing the SOF controllers that guarantee polynomial fuzzy systems stabilization. To demonstrate the effectiveness of the proposed polynomial fuzzy SOF H_∞ control, benchmark examples are provided for the new approach.     

LUNARES: lunar crater exploration with heterogeneous multi robot systems

The LUNARES (Lunar Crater Exploration Scenario) project emulates the retrieval of a scientific sample from within a permanently shadowed lunar crater by means of a heterogeneous robotic system. For the accomplished earth demonstration scenario, the Shakelton crater at the lunar south pole is taken as reference. In the areas of permanent darkness within this crater, samples of scientific interest are expected. For accomplishment of such kind of mission, an approach of a heterogeneous robotic team consisting of a wheeled rover, a legged scout as well as a robotic arm mounted on the landing unit was chosen. All robots act as a team to reach the mission goal. To prove the feasibility of the chosen approach, an artificial lunar crater environment has been established to test and demonstrate the capabilities of the robotic systems. Figure 1 depicts the systems in the artificial crater environment. For LUNARES, preexisting robots were used and modified were needed in order to integrate all subsystems into a common system control. A ground control station has been developed considering conditions of a real mission, requiring information of autonomous task execution and remote controlled operations to be displayed for human operators. The project successfully finished at the end of 2009. This paper reviews the achievements and lessons learned during the project.     

Characterization of Load Uncertainty in Unstructured Terrains and Applications to Battery Remaining Run‐time Prediction

Deployment of field robots in unstructured environments continues to rise, and the electrochemical battery remains the de facto standard for energy storage in robotic applications. However, robot mission planning, which relies on battery depletion time information, enforces conservative operation due to the lack of statistical rigor on the run‐time predictions. A two‐tier self‐supervised load characterization methodology for mobile robots operating in unstructured environments is proposed. Coupled with load characterization, a model‐based statistical battery remaining run‐time prediction algorithm utilizing particle filtering is presented. Given measured power loads during operation, the characterization algorithm employs Gaussian mixture modeling to cluster measured loads into a priori unknown regions. With clustered power demand regions, the computation of transition probabilities between the mixture models provides a jump Markov characterization of the historical power loads. An experimental study utilized Packbot data gathered during operation on general desert terrain. A particle filter prediction framework was shown to more accurately predict the remaining run‐time of the Packbot given the unstructured terrain compared to existing load‐averaging techniques. © 2013 Wiley Periodicals, Inc.     

Proxy-based position control of manipulators with passive compliant actuators: Stability analysis and experiments

In this work we introduce a position control scheme which is targeted at the enhancement of the safety of compliant joint robots. In addition to the necessity for accuracy and robustness that both serve as prerequisites for the successful performance of various tasks, the ability to safely handle unexpected events, such as communication failures or unintended interactions which may endanger the robot/human safety, is a paramount requirement. To achieve a smooth motion behaviour of compliant systems under different circumstances, damping control actions are essential. To this end, a novel proxy-based approach for compliant joint robots, integrated into a passivity-guaranteed controller, is proposed. The stability analysis of the proposed scheme is presented and the global asymptotic convergence, as well as the passivity of the control scheme, are analytically proven. The performance of the proposed approach is practically evaluated by means of experiments on a spatial robotic arm with passive compliant actuators, and is compared with that of a classical PD approach. Experimental results validate the ability of the proposed approach to inject damping in order to provide smooth and damped recovery when an interruption in task execution occurs.     

Robotic data mules for collecting data over sparse sensor fields

We present a robotic system for collecting data from wireless devices dispersed across a large environment. In such applications, deploying a network of stationary wireless sensors may be infeasible because many relay nodes must be deployed to ensure connectivity. Instead, our system utilizes robots that act as data mules and gather the data from wireless sensor network nodes. We address the problem of planning paths of multiple robots so as to collect the data from all sensors in the shortest time. In this new routing problem, which we call the data gathering problem (DGP), the total download time depends on not only the robots' travel time but also the time to download data from a sensor and the number of sensors assigned to the robot. We start with a special case of DGP in which the robots' motion is restricted to a curve that contains the base station at one end. For this version, we present an optimal algorithm. Next, we study the two‐dimensional version and present a constant factor approximation algorithm for DGP on the plane. Finally, we present field experiments in which an autonomous robotic data mule collects data from the nodes of a wireless sensor network deployed over a large field. © 2011 Wiley Periodicals, Inc.     

Fuzzy multi-criteria evaluation of industrial robotic systems

Industrial robots have been increasingly used by many manufacturing firms in different industries. While the number of robot manufacturers is also increasing with many alternative ranges of robots, potential end-users are faced with many options in both technical and economical factors in the evaluation of the industrial robotic systems. Industrial robotic system selection is a complex problem which many qualitative attributes must be considered. These kinds of attributes make the evaluation process hard and vague. Hierarchical structure is a good approach to describe a complicated system. This paper proposes a fuzzy hierarchical TOPSIS model for the multi-criteria evaluation of the industrial robotic systems. An application is presented with some sensitivity analyses by changing the critical parameters.     

求解柔性机器人车间调度问题的混合蚁群算法

在柔性作业车间调度问题的基础上,考虑多台搬运机器人执行不同工序在不同机床之间的搬运,形成柔性机器人作业车间调度问题,提出混合蚁群算法。用改进析取图对问题进行描述,使用混合选择策略、自适应伪随机比例规则和改进信息素更新规则优化蚁群算法,结合遗传算子完成机床选择和工序排序。使用一种多机器人排序算法完成搬运机器人分配和搬运工序排序。通过多组算例仿真测试并与其他算法进行比较,验证了算法的有效性和可靠性。     

基于改进免疫启发群聚集算法的群机器人自恢复方法

群机器人由许多简单的无差别的机器人组成,是多机器人系统的一个重要研究方向。虽然其相比个体机器人有良好的容错性和鲁棒性,但是在机器人发生局部故障--有信息交互能力但无驱动能力时,群机器人系统会受到影响。针 对这一问题,以基于生物免疫系统原理的肉芽肿形成算法为基础,引入离散粒子群算法选取最优的自恢复策略,使群机器人系统实现故障自恢复并更快更有效地完成任务。仿真实验结果表明该算法在群机器人自恢复系统中具有良好的效果。