Solving function distribution and behavior design problem for cooperative object handling by multiple mobile robots

This paper addresses the function distribution and behavior design problem for a multirobot system which incorporates a behavior-based dynamic cooperation strategy for object handling. The proposed multiple robot system is composed of a managing robot and homogeneous behavior-based robots. The cooperation strategy in this system is realized in two steps: designing the distributed robot's cooperative behavioral attributes according to the robot's abilities, and organizing these behavioral attributes so that team cooperation is realized. For indicating an incremental style of local behavior construction, an advanced design of cooperative behavior for coping with unknown disturbance is addressed. Additionally, two extended cooperation strategies designed for a path tracking task are described. These three strategies are based on the same concept on performing manipulation in coordination. Therefore, by considering the function distribution among the managing robot and worker robots, and considering behavior design of each worker robot, the proposed system is able to achieve the object handling task with different performances according to the task requirement, such as with or without path tracking and with or without contact with the environment. Experimental results demonstrate the applicability of the proposed system.     

Motion Planning for Two Robots of an Object Handling System Considering Fast Transition Between Stable States

Fast transition from a stable initial state to a stable handling state is important when multiple mobile robots grasp and transport a bulky and heavy object. In this paper, we present motion planning for two robots of an irregularly shaped object handling system considering fast transition between stable states. A cooperative object handling system consisting of a gripper robot equipped with a gripper and a lifter robot equipped with a lifter was first designed. Then, a strategy to realize fast transition between stable states by using the object handling system designed was proposed. While grasping and lifting an object off the ground, a gripper robot grasps and lifts up the object from one side to provide enough space for a lifter robot to lift the object off the ground cooperatively. Fast transition between stable states is formulated as a constraint optimization problem. The goal is to realize transition from a stable initial state to a stable handling state in a minimal amount of time. Experiments involving two robots and everyday objects were conducted. The two robots cooperatively obtained fast transition between stable states. The results illustrate the validity of the proposed method.     

Position estimation of a mobile robot using images of a moving target in intelligent space with distributed sensors

Latest advances in hardware technology and state-of-the-art of mobile robots and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. A mobile service robot requires the perception of its present position to co-exist with humans and support humans effectively in populated environments. To realize this, a robot needs to keep track of relevant changes in the environment. This paper proposes localization of a mobile robot using images recognized by distributed intelligent networked devices in intelligent space (ISpace) in order to achieve these goals. This scheme combines data from the observed position, using dead-reckoning sensors, and the estimated position, using images of moving objects, such as a walking human captured by a camera system, to determine the location of a mobile robot. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the ISpace. Using the a priori known path of a moving object and a perspective camera model, the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated robot's position are derived. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot, and the Kalman filtering scheme is used for the estimation of the mobile robot location. The proposed approach is applied for a mobile robot in ISpace to show the reduction of uncertainty in determining the location of a mobile robot, and its performance is verified by computer simulation and experiment.     

Human robot cooperation with compliance adaptation along the motion trajectory

In this paper we propose a novel approach for intuitive and natural physical human–robot interaction in cooperative tasks. Through initial learning by demonstration, robot behavior naturally evolves into a cooperative task, where the human co-worker is allowed to modify both the spatial course of motion as well as the speed of execution at any stage. The main feature of the proposed adaptation scheme is that the robot adjusts its stiffness in path operational space, defined with a Frenet–Serret frame. Furthermore, the required dynamic capabilities of the robot are obtained by decoupling the robot dynamics in operational space, which is attached to the desired trajectory. Speed-scaled dynamic motion primitives are applied for the underlying task representation. The combination allows a human co-worker in a cooperative task to be less precise in parts of the task that require high precision, as the precision aspect is learned and provided by the robot. The user can also freely change the speed and/or the trajectory by simply applying force to the robot. The proposed scheme was experimentally validated on three illustrative tasks. The first task demonstrates novel two-stage learning by demonstration, where the spatial part of the trajectory is demonstrated independently from the velocity part. The second task shows how parts of the trajectory can be rapidly and significantly changed in one execution. The final experiment shows two Kuka LWR-4 robots in a bi-manual setting cooperating with a human while carrying an object.     

Stability and Control of Collective Systems

In this paper, decentralized, distributed feedback control laws are presented for cooperative robotic systems whose task is to localize unknown sources. The control laws follow from a second order representation of the source field. The stability of the proposed feedback control laws for the individual robots, and for the entire robot collective, is demonstrated using Lyapunov's direct method and a vector Lyapunov approach. Additional feedback control laws are proposed to achieve an additional level of coordination. In particular, control laws that achieve desired formations surrounding a localized source are developed.     

Realization of a hydraulic actuated biped robot walking without double support phase

This paper introduced a new walking pattern generation method for biped robots without active roll joint at the ankle and described a simple walking pattern generation method for the robot without using ZMP (Zero Moment Point) information directly. Firstly, the paper introduced a hydraulic actuated biped robot with eight degrees of freedom, which had payload capacity. Secondly, the paper provided a dynamic balance control method in the lateral plane. Not as the inverted pendulum model, this control method was also available for biped robot without active roll joint at the ankle. Thirdly, in order to decrease the vibration, the paper tried to keep the robot walking with an approximate constant speed in the frontal direction. Finally, weight loading experiments in the MD.DAMS simulation environment and physical prototype empty load experiments were used to verify the effectiveness of the proposed walking pattern methods.     

Learning cooperative grasping with the graph representation of a state-action space

In this paper we present a method for two robot manipulators to learn cooperative tasks. If a single robot is unable to grasp an object in a certain orientation, it can only continue with the help of other robots. The grasping can be realized by a sequence of cooperative operations that re-orient the object. Several sequences are needed to handle the different situations in which an object is not graspable for the robot. It is shown that a distributed learning method based on a Markov decision process is able to learn the sequences for the involved robots, a master robot that needs to grasp and a helping robot that supports him with the re-orientation. A novel state-action graph is used to store the reinforcement values of the learning process. Further an example of aggregate assembly shows the generality of this approach.     

Reflexive stability control framework for humanoid robots

In this paper we propose a general control framework for ensuring stability of humanoid robots, determined through a normalized zero-moment-point (ZMP). The proposed method is based on the modified prioritized kinematic control, which allows smooth and continuous transition between priorities. This, as long as the selected criterion is met, allows arbitrary joint movement of a robot without any regard of the consequential movement of the ZMP. On the other hand, it constrains the movement when the criterion approaches a critical condition. The critical condition thus triggers a reflexive, subconscious behavior, which has a higher priority than the desired, conscious movement. The transition between the two is smooth and reversible. Furthermore, the switching is encapsulated in a single modified prioritized task control equation. We demonstrate the properties of the algorithm on two human-inspired robots developed in our laboratory; a human-inspired leg-robot used for imitating human movement and a skiing robot.     

Distributed object transportation on a desired path based on Constrain and Move strategy

In this paper, a distributed strategy to move objects on different arbitrary paths in a 2D plane is proposed and analyzed. This algorithm which is based on Constrain and Move strategy [M.N. Ahmadabadi, E. Nakano, A Constrain and Move approach to distributed object manipulation, IEEE Trans. Robotics Automation 17 (2) (2001) 157], organizes the robots in two groups. The object manipulation task also is decomposed to two different tasks. The task given to one group is control of linear velocity and that assigned to the other group is control of angular velocity of the object. The independence of these tasks makes the design of the distributed architecture of the team possible. To calculate each robot's desired velocity, a simple method using Constrain and Move strategy and robot's local sensors is developed. To prevent small errors in the robot sensory system from affecting the system performance, limited compliance is assumed in robot arms. The basic behaviors of the robots are presented. Moreover, simulation results are given to verify the proposed strategy.     

CDCSMA-CD communication method for cooperative robot systems

Robot cooperation means 'work-accomplishment action with collaboration of multiple robots by applying shared information, transmitted from a robot to others in a system'. The definition implies that efficiency of a cooperative robot system depends directly upon two main factors, one is communication among the robots and the other is movement of the robots. Robots with appropriate cooperation are expected to work efficiently. The authors propose here an efficient communication method for a cooperative robots system, Code Division Carrier Sensing Multiple Accesses with Collision Detection (CDCSMA-CD). CDCSMA-CD, differing from communication methods in the past, is specifically designed for a cooperative robot system so it can be applied appropriately for both point-to-point and broadcast communication. Within this paper, the principle and hardware structure of the proposed CDCSMA-CD are described. The efficiency of CDCSMA-CD, compared with other communication methods, is then evaluated and discussed.     

智能决策改进的四足机器人ZMP爬行步态算法

提出了一种基于反馈控制和贪婪决策的四足机器人爬行步态规划算法。该算法利用机载惯性传感器IMU（Inertial Measurement Unit）来实时计算零力矩点和姿态角,以稳态裕度为指标在支撑平面内实时规划期望零力矩点（Zero Moment Point,ZMP）轨迹,结合非线性反馈控制器实现对机体ZMP点的连续平滑调节,保证机器人在按给定速度矢量进行连续爬行的同时具有抵抗一定外力扰动的能力。步态规划采用动态步态周期,基于机器人结构约束和贪婪决策实现跨腿的自动触发,提高了步态自适应性。最终通过样机行走实验验证了所提算法应用于微型四足机器人中的可行性,机器人实现了在平坦地面上稳定地全向行走和旋转,所提算法同时兼顾了自适应性和稳定裕度。     

Adaptive task assignment for multiple mobile robots via swarm intelligence approach

This paper describes an adaptive task assignment method for a team of fully distributed mobile robots with initially identical functionalities in unknown task environments. A hierarchical assignment architecture is established for each individual robot. In the higher hierarchy, we employ a simple self-reinforcement learning model inspired by the behavior of social insects to differentiate the initially identical robots into “specialists” of different task types, resulting in stable and flexible division of labor; on the other hand, in dealing with the cooperation problem of the robots engaged in the same type of task, Ant System algorithm is adopted to organize low-level task assignment. To avoid using a centralized component, a “local blackboard” communication mechanism is utilized for knowledge sharing. The proposed method allows the robot team members to adapt themselves to the unknown dynamic environments, respond flexibly to the environmental perturbations and robustly to the modifications in the team arising from mechanical failure. The effectiveness of the presented method is validated in two different task domains: a cooperative concurrent foraging task and a cooperative collection task.     

Modeling and bio-mimetic control for whole-arm dynamic cooperative manipulation

This paper studies modeling and bio-mimetic control of a three-dimensional 8-d.o.f. whole-arm cooperative manipulation system using sensitive skin. A sphere is considered here as a manipulated object. The control law is designed based on integration of voluntary movement and reflex considering the system's redundancy. The voluntary task of holding the object safely is realized via multi-point impedance control at the four contact points with the object using the contact force information from the sensitive skin. A reflex is introduced as a regulation problem of the direction between the points of end-effectors and elbows to determine the robot system's posture uniquely and to adapt to external disturbances. The solution of the redundant control is formulated and derived from the optimization point of view for different cases of the output function's dimensions. Further, desired functions for voluntary movement and reflex are adjusted according to the task situations. The validity of the proposed method is investigated by numerical simulations.     

Automatic cooperative disassembly robotic system: Task planner to distribute tasks among robots

This paper presents a task planner based on decision trees. Two different types of cooperative tasks are described: common task and parallel task. In the first type of task two or more robots are required to accomplish the task. In the second type, several tasks can be performed in parallel by different robots to reduce the total disassembly time. The planner presented is based on a hierarchical representation of the product and performs the distribution of the tasks among robots using decision trees. The system takes into consideration the work area of each robot and its own characteristics. The work cell can be composed of j robotic manipulators. Finally, a practical application of a PC disassembly system is shown.     

基于能效优化的两足机器人步态控制方法

针对高能耗导致的两足机器人实用化障碍,提出了一种全新的、系统化的步态能效优化控制方法.基于两足机器人运动的重要能耗指标(平均功率、平均功率偏差、平均力矩损耗),提出了能耗预估策略和能效优化算法,获取了零力矩点(ZMP)稳定区域内的能耗极小值.沿着能耗极小值所对应的上体轨迹对机器人步态实施能效优化控制,最终获得满足ZMP稳定判据的低能耗步态.仿真结果证明,该方法能够有效降低机器人能耗并保持其稳定性.     

Adaptive control of redundant multiple robots in cooperative motion

A redundant robot has more degrees of freedom than what is needed to uniquely position the robot end-effector. In practical applications the extra degrees of freedom increase the orientation and reach of the robot. Also the load carrying capacity of a single robot can be increased by cooperative manipulation of the load by two or more robots. In this paper, we develop an adaptive control scheme for kinematically redundant multiple robots in cooperative motion.In a usual robotic task, only the end-effector position trajectory is specified. The joint position trajectory will therefore be unknown for a redundant multi-robot system and it must be selected from a self-motion manifold for a specified end-effector or load motion. In this paper, it is shown that the adaptive control of cooperative multiple redundant robots can be addressed as a reference velocity tracking problem in the joint space. A stable adaptive velocity control law is derived. This controller ensures the bounded estimation of the unknown dynamic parameters of the robots and the load, the exponential convergence to zero of the velocity tracking errors, and the boundedness of the internal forces. The individual robot joint motions are shown to be stable by decomposing the joint coordinates into two variables, one which is homeomorphic to the load coordinates, the other to the coordinates of the self-motion manifold. The dynamics on the self-motion manifold are directly shown to be related to the concept of zero-dynamics. It is shown that if the reference joint trajectory is selected to optimize a certain type of objective functions, then stable dynamics on the self-motion manifold result. The overall stability of the joint positions is established from the stability of two cascaded dynamic systems involving the two decomposed coordinates.     

Virtual target tracking of mobile robot and its application to formation control

A virtual target tracking approach is proposed for kinematic control of mobile robot. In the controller, linear and angular velocity inputs are generated by using the local data of robot position and orientation along with the estimated velocity of target object. Applying the proposed approach to a cooperative robot group with arbitrary number of multiple mobile robots, it is possible to create various robot formations for cooperative navigation and tracking of moving object. The developed controller is shown to be stable and convergent through theoretical proof and a series of experiments.     

Nonlinear coupling tracking control for underactuated construction lifting robots with load hoisting/lowering under initial input saturations

Underactuated construction lifting robots, which have been widely concerned by erudite researchers, always contain load hoisting/lowering motion. When the cable length is utilized as a variable, construction lifting robots produce violent load swing, which affects the construction safety undoubtedly and brings great challenges to the development of the controller. Moreover, most existing controllers may not take into account issues, such as initial input saturations and poor ability to suppress load swing, and they may utilize linearization or approximation. Inspired by these phenomena, a nonlinear coupling tracking controller for underactuated construction lifting robots with load hoisting/lowering under initial input saturations is proposed. With reference to expected trajectories to ensure the smooth operation of the construction lifting robot system, the initial input saturations are considered to make the trolley and cable start stably, respectively; a coupling signal, which contains actuated variables and underactuated variables, is constructed to improve the transient control performance of construction lifting robots. Combined with theoretical derivation, simulation, and experimental verification, the proposed controller achieves superior control performance, which ensures the accurate positionings of the system, and suppresses and eliminates the load swing effectively, so as to ensure the safe construction; the proposed controller admits outstanding robustness with respect to the changes of system parameters and the adverse effects of external disturbances. The proposed controller provides a novel antiswing strategy for construction lifting robots with load hoisting/lowering, which possesses excellent practical significance.     

Time-optimal trajectories for cooperative multi-manipulator systems

We present two schemes for planning the time-optimal trajectory for cooperative multi-manipulator system (CMMS) carrying a common object. We assume that the desired path is given and parameterizable by an arclength variable. Both approaches take into account the dynamics of the manipulators and object. The first approach employs linear programming techniques, and it allows us to obtain the time-optimal execution of the given task utilizing the maximum torque capacities of the joint motors. The second approach is a sub-time-optimal method that is computationally very efficient. In the second approach the given load is divided into a share for each robot in the CMMS in a manner in which the trajectory acceleration/deceleration is maximized, hence the trajectory execution time is minimized. This load distribution approach uses optimization schemes that degenerate to a linear search algorithm for the case of two robots manipulating a common load, and this results in significant reduction of computation time. The load distribution scheme not only enables us to reduce the computation time, but also gives us the possibility of applying this method in real-time planning and control of CMMS. Further, we show that for certain object trajectories the load distribution scheme yields truly time-optimal trajectories.     

Cooperative task excecution of a search and rescue mission by a multi-robot team

Rescue robots have proved to be an extremely useful work partner for urban search and rescue (USAR) missions. Human rescuers who carry out these missions frequently enter dangerous zones to search for survivors; however, due to the unstable nature of collapsed buildings or objects, their lives may also be threatened. For this reason, in order to reduce life-threatening risks, rescue robots are deployed to carry out the job instead. Rescuers can now operate the robots at a safe place while the missions are carried out. When the robots have gathered enough information about the location of the victims and data about their physical conditions, rescuers can then enter the disaster site with enough knowledge to avoid harm and rescue the victims in the shortest time possible. In this paper, we introduce examples of 'effective multiple robot cooperative activities' and 'a study of the number of robots and operators in a multi-robot team' from our experiences gained from participating in RoboCup Rescue competitions.