This paper introduces a control architecture that enables a robotic system to ensure the safety of human operators entering its workspace. The proposed method utilizes an appropriate metric to measure safety levels and adjusts the robot’s motion to maintain this metric above a minimum threshold. To guarantee safety, the robot scales down and deviates from its intended path. For redundant robots, internal motion is exploited to enhance safety levels further. The approach is incorporated into a Hierarchical Quadratic Programming control framework, allowing the robot to address other control objectives simultaneously, such as handling joint limits. Experimental results with a dual-arm mobile robot developed as part of the EU-funded CANOPIES project demonstrate the effectiveness of the proposed method.Note to Practitioners—This paper was motivated by the problem of ensuring human safety in unstructured environments shared with human operators. We propose a control architecture that allows complex dual-arm robotic systems to operate effectively in such scenarios. The devised architecture gives the robot the capability to slow down a trajectory to follow as well as to deviate from a nominal path to keep a human operator safe. We tested the devised approach in a precision farming setting; however, it can be adopted in any human-robot interaction scenario.

Bearing Only Tracking of an underwater moving acoustic source employing multiple moving sensors is addressed in this paper. The vehicles need to communicate to exchange their local measurements coming from Passive Acoustic Monitoring sensors with an inevitable communication latency and packet loss, which has to be to be properly addressed in the algorithm. Additionally, The limited velocity of the sound in water causes the sensors to receive asynchronous data caused by the sound propagation delay. A distributed, iterative, optimization algorithm taking into account all these aspects is proposed and numerically verified on realistic simulations to validate the proposed approach.

Set-Based Multi-Task Priority is a recent framework to handle inverse kinematics for redundant structures. Both equality tasks, i.e., control objectives to be driven to a desired value, and set-bases tasks, i.e., control objectives to be satisfied with a set/range of values can be addressed in a rigorous manner within a priority framework. In addition, optimization tasks, driven by the gradient of a proper function, may be considered as well, usually as lower priority tasks. In this paper the proper design of the tasks, their priority and the use of a Set-Based Multi-Task Priority framework is proposed in order to handle several constraints simultaneously in real-time. It is shown that safety related tasks such as, e.g., joint limits or kinematic singularity, may be properly handled by consider them both at an higher priority as set-based task and at a lower within a proper optimization functional. Experimental results on a 7DOF Jaco2arm with and without the proposed approach show the effectiveness of the proposed method.

In this paper, a distributed scheme to allow a human operator to physically interact with a multi-manipulator system is devised. Manipulators are tightly connected to a rigid object and a human operator interacts with it to perform, for example, a cooperative transportation task. The strategy foresees two layers. The top layer is in charge of assigning a compliant behaviour to the object through an admittance model whose reference trajectory is dynamically adjusted to regulate the human-object interaction force. Moreover, since the parameters of the dynamic model of the human arm end-point are supposed to be time-varying and completely unknowns with unknown bounds, a robust adaptive control is envisaged in this layer. The output of this layer is a desired object trajectory which is tracked by the bottom layer. In detail, the latter resorts to a robust adaptive control strategy to both track the object trajectory and control the internal stresses exerted by the manipulators on the object which unavoidably arise due to dynamic and kinematic uncertainties and synchronization errors. Simulations involving a setup with three dual-arm Movo mobile robots corroborate the theoretical findings.

In this paper we present a framework that allows the motion control of a robotic arm automatically handling different kinds of safety-related tasks. The developed controller is based on a Task-Priority Inverse Kinematics algorithm that allows the manipulator's motion while respecting constraints defined either in the joint or in the operational space in the form of equality-based or set-based tasks. This gives the possibility to define, among the others, tasks as joint-limits, obstacle avoidance or limiting the workspace in the operational space. Additionally, an algorithm for the real-time computation of the minimum distance between the manipulator and other objects in the environment using depth measurements has been implemented, effectively allowing obstacle avoidance tasks. Experiments with a Jaco2manipulator, operating in an environment where an RGB-D sensor is used for the obstacles detection, show the effectiveness of the developed system.

In this paper we present an architecture for the operation of an assistive robot finally aimed at allowing users with severe motion disabilities to perform manipulation tasks that may help in daily-life operations. The robotic system, based on a lightweight robot manipulator, receives high level commands from the user through a Brain-Computer Interface based on P300 paradigm. The motion of the manipulator is controlled relying on a closed loop inverse kinematic algorithm that simultaneously manages multiple set-based and equality-based tasks. The software architecture is developed relying on widely used frameworks to operate BCIs and robots (namely, BCI2000 for the operation of the BCI and ROS for the control of the manipulator) integrating control, perception and communication modules developed for the application at hand. Preliminary experiments have been conducted to show the potentialities of the developed architecture.

In this paper a three layer control architecture for multiple aerial robotic manipulators is presented. The top layer, on the basis of the desired mission, determines the end-effector desired trajectory for each manipulator, while the middle layer is in charge of computing the motion references in order to track such end-effectors trajectories coming from the upper layer. Finally the bottom layer is a low level motion controller, which tracks the motion references. The overall mission is decomposed in a set of elementary behaviors which are combined together, through the Null Space-based Behavioral (NSB) approach, into more complex compounds behaviors. The proposed framework has been tested conducting an experimental campaign.

In this paper, an impedance control scheme for aerial robotic manipulators is proposed, with the aim of reducing the end-effector interaction forces with the environment. The proposed control has a multi-level architecture, in detail the outer loop is composed by a trajectory generator and an impedance filter that modifies the trajectory to achieve a complaint behaviour in the end-effector space; a middle loop is used to generate the joint space variables through an inverse kinematic algorithm; finally the inner loop is aimed at ensuring the motion tracking. The proposed control architecture has been experimentally tested.

This work tackles the problem of controlling an Unmanned Aerial Vehicle equipped with a robotic Manipulator and it has been developed within the framework of the EU-funded ARCAS (Aerial Robotics Cooperative Assembly System) project. A behavioral control, based on the Null Space-based Behavioral (NSB) paradigm, is proposed to tackle the coordination between the arm and vehicle motions. To this aim, a set of basic functionalities (called elementary behaviors) are designed and combined in a priority order to attain complex tasks (called compound behaviors). The proposed controller has been experimentally validated on a multirotor aircraft with an attached 6 Degree of Freedoms manipulator. Two experimental case studies, involving several compound behaviors, have been reported and the results show the effectiveness of the approach.

In this paper, an adaptive trajectory tracking controller for quadrotor MAVs is presented. The controller exploits the common assumption of a faster orientation dynamics w.r.t. the translational one, and is able to asymptotically compensate for parametric uncertainties (e.g., displaced center of mass), as well as external disturbances (e.g., wind). The good performance of the proposed controller is then demonstrated by means of an extensive experimental evaluation performed with a commercially-available quadrotor MAV.

A coordination mechanism to achieve the sampling task of static or dynamic fields by means of a system composed by multiple mobile robots is addressed in this paper. The problem is the estimation of a scalar field. To this aim in a probabilistic framework a solution is proposed that takes into account several constraints. The attention is focused on the vehicles motion generation and the developed strategy is designed for multiple, autonomous and distributed robots. It makes use of the Voronoi tessellation's properties to automatically distribute the vehicles' motion and of the Null-Space-Behavioral control to handle eventually conflicting motion tasks (as reaching a given point while avoiding obstacles). The algorithm can be tailored based on the communication and computational capabilities of the robots. A discussion and possible counterexamples of the applications of existing approaches are provided in the paper. Numerical simulations illustrate the results.

The paper studies the observability properties of the relative localization of two Autonomous Underwater Vehicles (AUVs) equipped with depth sensors, linear/angular velocity sensors, and communication devices with range measurement. The conditions that ensure observability of the linearized model and locally weak observability of the nonlinear system are derived. An Extended Kalman Filter is then designed aimed at estimating the relative position between two AUVs. Simulations in 3D and reconstruction from experimental data in 2D provide a numerical validation of the analysis.

Coordinated control of marine vehicles poses challenging problems, among them the possibility to use the vehicles, in addition to their nominal mission, also to achieve a relative localization task. To the purpose, the use of a surface, GPS-equipped, vehicle and one or several underwater vehicles may be envisaged. The latters can communicate among them by acoustic modems; those devices can also be used as ranging measurement units thus providing an additional information that, together with the common sensor equipment for marine vehicles, might be used for relative localization. This paper investigates how the vehicles' movements can be commanded in order to help the relative localization by a proper analysis of the system observability and a corresponding proper definition of the vehicles movements; critical situations for the relative observability, that corresponds to common movements, are then avoided. Numerical simulations on the mathematical model of the Fòlaga hybrid underwater vehicle confirm the effectiveness of the proposed coordinated behavioral approach.

We present a study on the use of cooperative robots to execute a caging mission on the water's surface. In particular, we consider the problem of using two robotic boats (under-actuated autonomous surface vessels) connected with a floating rope, to `capture' a floating object from a known location on the water's surface and 'shepherd' it to a designated position. This paper focuses on the cooperative control strategy of the two vessels. Each vessel's behavior is governed by a supervisor software module that handles the communication with the other vessel and controls all elementary tasks that compose the overall mission. The elementary tasks, specifically developed for under-actuated vessels, are arranged by priority, and merged using a behavior-based approach, namely the Null-Space based Behavioral control. The proposed technique is validated by field experiments with two autonomous robotic boats on the surface of a lake.

This paper presents the application of the Null-Space based Behavioral (NSB) approach to the motion control of a non-holonomic mobile robot with velocity saturated actuators. In particular, the proposed solution aims at managing actuator velocity saturations by dynamically scaling task velocity commands so that the hierarchy of task priorities is preserved in spite of actuator velocity saturations. The approach is tested on a specific case study where the NSB approach elaborates the motion directives for a mobile robot that has to reach a target while avoiding a punctual obstacle. The approach is validated by numerical simulations and by experimental results with a non-holonomic mobile robot.

Standard kinematics prioritized task based motion control solutions do not take into account the physical limitations in terms of maximum actuator speed of robots. In this paper, a prioritized task based kinematics control solution is presented that, under given conditions on the kind of concurrent tasks to be pursued, guarantees task error stability and convergence. Moreover the joint velocities are guaranteed to be bounded by a desired threshold. As for other a null-space projection techniques known in the literature, joint speed commands are computed in such a way that lower priority tasks do not interfere with higher priority ones in the assumption that joint speeds can be arbitrarily large: in addition, if joint speeds are to be bounded by a desired value, joint velocity commands are limited by dynamically chosen values depending on the task priority. As a result, joint velocities are always bounded such that, if necessary, higher priority tasks are executed first.

This paper presents the application of the null-space based behavioral (NSB) approach to the motion control of a team of mobile robots with velocity saturated actuators. In particular, the proposed solution aims at managing actuator velocity saturations by dynamically scaling task velocity commands so that the hierarchy of task priorities is preserved in spite of actuator velocity saturations. The approach is tested on a specific case study where the NSB elaborates the motion directives for a team of six mobile robots that has to entrap and to escort a target. The approach is validated by numerical simulations and by experimental results.

In this paper the flocking problem for a multi-robot system, consisting in making the robots of a team grouping together, is addressed. The flocking is achieved resorting to the Null-Space-based Behavioral (NSB) control by defining very simple behaviors for each robot of the team and by properly arranging these behaviors in priority. The NSB algorithm, making the robots using only local information, successfully achieves the flocking with or without a rendez-vous point and in eventual presence of obstacles. Extensive simulations and experiments using differential-drive mobile robots prove the effectiveness of the proposed algorithm.

In this paper, two experimental case studies performed with a multi-robot system made of 6 Khepera II mobile robots are presented. The experiments, performed at the laboratory LAI (Laboratorio di Automazione Industriale) of the Universita degli Studi di Cassino, are aimed at testing the performances and the robustness of a behavior-based technique, namely the null-space-based behavioral control (NSB), while executing different kinds of missions. In particular, the NSB approach, based on an inverse kinematic technique inherited by industrial manipulator applications, has been developed to control a generic team of autonomous vehicles and it has been implemented on a centralized architecture to control, at a kinematic level, a platoon of autonomous mobile robots.

One important problem in autonomous robot navigation is the effective following of an unknown path traced in the environment in compliance with the kinematic limits of the vehicle, i.e., bounded linear and angular velocities and accelerations. In this case, the motion planning must be implemented in real-time and must be robust with respect to the geometric characteristics of the unknown path, namely curvature and sharpness. To achieve good tracking capability, this paper proposes a path following approach based on a fuzzy-logic set of rules which emulates the human driving behavior. The input to the fuzzy system is represented by approximate information concerning the next bend ahead the vehicle; the corresponding output is the cruise velocity that the vehicle needs to attain in order to safely drive on the path. To validate the proposed algorithm two completely different experiments have been run: in the first experiment, the vehicle has to perform a lane-following task acquiring lane information in real-time using an onboard camera; in the second, the motion of the vehicle is obtained assigning in real-time a given time law. The obtained results show the effectiveness of the proposed method

In this paper a calibration technique aimed at identifying the odometric parameters of differential-drive mobile robots is proposed. The proposed algorithm is based on two successive least-squares estimations based on the continuous-time kinematic equations of motion; the time-discretization error, thus, is avoided. The use of the least-squares technique is made possible by observing a linear mapping between the unknowns and the measurements and it is not the results of a linearization. Another advantage of the proposed technique is that no predefined path is required, i.e., the robot can move under a preferred navigation algorithm. The basic technique makes use of video-camera measurements and absolute position readings of the wheels' encoders, the use of different sensors and measurements of the wheels velocities is also discussed. Experimental results with the mobile robot Khepera II confirm the effectiveness of the proposed technique

In this paper the application of a behavior-based control approach, namely the null-space-based behavioral control, to coordinate a fleet of autonomous surface vessels is presented. The NSB can be considered as a centralized guidance system aimed at driving the fleet in complex environments while simultaneously performing multiple tasks, i.e., obstacle avoidance or keeping a formation. In order to apply the guidance system to a fleet of underactuated surface vessels, the NSB works in combination with a low-level maneuvering control that, taking care of the dynamics of the vessels, elaborates the motion commands to generate the generalized forces at the actuators. The guidance system has been simulated in the accomplishment of a mission in presence of obstacles and sea current in the environment

In this paper, an approach to control the motion of a platoon of autonomous vehicles is presented. The proposed technique is based on the definition of suitable task functions that are handled in the framework of singularity-robust task-priority inverse kinematics. The algorithm is implemented by a two-stage control architecture such that intervehicle communication is not required. The effectiveness of the approach is investigated by means of numerical simulation case studies

This paper develops an algorithm for odometry calibration of differential-drive mobile robots. As a first step, the kinematic equations are written so as to underline linearity in a suitable set of unknown parameters; then, the least-squares method is applied to estimate them. The wide literature on the least-squares formulation can thus be exploited; suitability of the data can be numerically verified. The proposed technique has been implemented on the Khepera II mobile robot; the obtained results confirm the effectiveness of the proposed calibration method also in comparison to other existing approaches.

This paper investigates the implementation of a wireless mobile ad-hoc network to guarantee that an autonomously driven mobile vehicle remains connected to a limited-coverage base antenna during its motion. To the purpose, the use of a platoon of mobile robots is proposed to carry a number of repeater antennas; these must be suitably moved to dynamically ensure a multi-hop communication link to the vehicle that extends outside the area covered by the sole base antenna. Self configuration of the robots' platoon is then achieved by a singularity-robust task-priority inverse kinematics algorithm via the definition of suitable task functions. The obtained simulation results show the effectiveness of the proposed approach.

For a mobile robot, odometry calibration consists of the identification of a set of kinematic parameters that allow reconstructing the vehicle's absolute position and orientation starting from the wheels' encoder measurements. This paper develops a systematic method for odometry calibration of differential-drive mobile robots. As a first step, the kinematic equations are written so as to underline linearity in a suitable set of unknown parameters; thus, the least-squares method can be applied to estimate them. A major advantage of the adopted formulation is that it provides a quantitative measure of the optimality of a test motion; this can be exploited to drive guidelines on the choice of the test trajectories and to evaluate accuracy of a solution. The proposed technique has been experimentally validated on two different mobile robots and, in one case, compared with other existing approaches; the obtained results confirm the effectiveness of the proposed calibration method.

In this paper the fault tolerance capabilities of a kinematic control technique for platoons of autonomous vehicles are investigated. The proposed technique is based on the definition of suitable task functions that are handled in the framework of singularity-robust task-priority inverse kinematics algorithms. The control scheme is tested in simulation in a mission requiring 8 vehicles to entrap a moving target in presence of obstacles to be avoided; the mission is accomplished despite the failure of one vehicle that, once stopped, becomes an obstacle to be avoided itself.

A novel adaptive control law for the end-effector tracking problem of underwater vehicle-manipulator systems (UVMSs) is presented in this paper. By exploiting the serial-chain kinematic structure of the UVMS, the overall control problem is decomposed in a set of elementary control problems, each of them formulated with respect to a single rigid body in the system. The proposed approach results in a modular control scheme which simplifies application to UVMSs with a large number of links, reduces the required computational burden, and allows efficient implementation on distributed computing architectures. Furthermore, the occurrence of kinematic and representation singularities is overcome, respectively, by expressing the control law in body-fixed coordinates and representing the attitude via the unit quaternion. To show the effectiveness of the proposed control strategy, a simulation case study is developed for a vehicle in spatial motion carrying a six-degree-of-freedom manipulator.

In this paper a strategy to control the motion of platoon of autonomous vehicles is presented. The proposed technique is based on the definition of suitable task functions that are handled in the framework of singularity-robust task-priority inverse kinematics. The algorithm is implemented by two-stage control architecture such that inter-vehicle communication is not required. The possible definition of several task functions of interest is discussed and the effectiveness of the approach is investigated by means of numerical simulation case studies.

The problem of redundancy resolution and motion coordination between the vehicle and the manipulator in underwater vehicle-manipulator systems (UVMSs) is addressed in this paper. UVMSs usually possess more degrees of freedom than those required to perform end-effector tasks; therefore, they are redundant systems and kinematic control techniques can be applied aimed at achieving additional control objectives besides tracking of the end-effector trajectory. In this paper, a task-priority inverse kinematics approach to redundancy resolution is merged with a fuzzy technique to manage the vehicle-arm coordination. The fuzzy technique is used both to distribute the motion between vehicle and manipulator and to handle multiple secondary tasks. Numerical case studies are developed to demonstrate effectiveness of the proposed technique.

The presence of joint velocity and acceleration limits must be taken into account by the inverse kinematics of robot manipulators, so as to avoid incorrect task execution when these are violated. To solve this problem, a novel algorithmic approach to kinematic control is presented in this paper, which guarantees that the joint variables do not overtake their limits. The proposed technique is based on a new second-order inverse kinematics algorithm, which enables the handling of velocity and acceleration constraints while tracking the desired end-effector path. The goal is achieved by suitably slowing down the task-space trajectory via a time warp when joints limits are encountered. The proposed method is designed for online applications, i.e., the desired trajectory is not known in advance, and requires a light computational burden. The application of the proposed approach is finally illustrated in experiments implemented on a six-degree-of-freedom industrial robot manipulator.

This paper presents an experimental study concerning the application of a real-time motion planning algorithm to a unicycle-like mobile robot. The desired trajectory to be followed by the mobile robot in presence of bounds on the linear/angular velocities and accelerations is available online. Moreover, with the respect to the kinematic constraints, the desired path has to be kept as long as possible. The implemented algorithm is based on a discrete-time kinematic control which implements a warping of the time law based on the definition of a virtual time. In addition, a fuzzy inference system handles the additional information given by the difference between the virtual and real time in order to exploit the knowledge in advance of the desired path. The experimental results confirm the effectiveness of the adopted algorithm.

An adaptive control law for autonomous underwater vehicles (AUVs) is presented. Usually, the control laws are designed with respect to a mathematical model expressed either in the Earth-fixed frame or in the vehicle-fixed frame. These two approaches, however, do not take into account the different origin of the effects that can affect the steady state errors: namely, the restoring generalized forces and the ocean current. With the use of a suitable adaptive action those effects can be properly taken into account as is shown in the paper.

The interaction of underwater vehicle-manipulator systems (UVMSs) with the environment is affected by several design constraints such as uncertainty in the model knowledge, presence of hydrodynamic effects, kinematic redundancy of the system, and poor performance of vehicle's actuating system. The paper presents an external force control scheme for UVMSs that does not require dynamic compensation; however, it can benefit from the knowledge of part of the dynamic model. The possible occurrence of loss of contact due to vehicle movement during the task, is also taken into account. A numerical case study shows the application of the proposed technique in a given task.

The goal of the paper is the application of a geometrically consistent impedance concept to control interaction with the environment of a rigid object manipulated by a dual-robot system. A six-DOF impedance is specified at the object level to confer a compliant behavior for both the translational and the rotational motion when an external force and moment occurs at the contact. Geometric consistency is ensured thanks to the use of the unit quaternion to describe object frame orientation. The resulting object motion is decomposed into the equivalent motions at the end effectors of the two robots, via a task-oriented formulation. The control scheme is derived according to an inverse dynamics strategy with adoption of an inner motion loop providing robustness to unmodeled dynamics and disturbances. Experimental results on the two industrial robots available in the lab are discussed.

A navigation system for real-time path planning and obstacle avoidance of an autonomous underwater vehicle is presented. The vehicle is designed to accomplishing two missions: pre-deployment survey of sea bottom, and visual inspection of pipelines. In the first mission the navigation system must be able to track a predefined path while avoiding the unplanned occurrence of obstacles. In the second mission the navigation system must track a pipeline by locally reconstructing its location from visual information; also in this case, the unplanned occurrence of obstacles must be handled. Furthermore, the navigation system must properly take into account the presence of ocean current and some drastic constraints due to sensor and actuator characteristics.

An explicit force control scheme for underwater vehicle-manipulator systems is presented. Several major problems of underwater robotics are taken into account; namely, uncertainty in the model knowledge, presence of hydrodynamic effects, kinematic redundancy of the system, and poor performance of the vehicle's actuating system. The possible occurrence of loss of contact due to vehicle movement during the task is also discussed. Extensive dynamic simulations prove the effectiveness of the proposed control algorithm.

An underwater vehicle-manipulator system (UVMS) usually has more degrees of freedom than those required to attain given end-effector postures. Therefore, the UVMS is a redundant system and kinematic control algorithms can be applied aimed at achieving additional control objectives such as energy savings or increase of system manipulability. This paper presents a task-priority inverse kinematics approach to redundancy resolution for a UVMS. Three case studies are developed to demonstrate the effectiveness of the technique in different applications.

In the framework of parallel force/position control for a robot manipulator in contact with a compliant environment, a new scheme is proposed which is aimed at controlling the end-effector force in the face of uncertainty on the surface stiffness. The controller is of inverse dynamics type with a force feedforward action. Adaptation to unknown stiffness is achieved by resorting to a suitable estimate update law driven by the force error. Tracking of both position along the unconstrained directions and force along the constrained direction is ensured. Experimental results on an industrial robot with open control architecture are presented.

Practical application of the task-priority redundancy resolution technique must deal with the occurrence of kinematic and algorithmic singularities. The aim of this paper is twofold. First, the application of existing singularity-robust methods to the case of kinematically redundant arms is studied. Then, a new task-priority redundancy resolution technique is developed that overcomes the effects of algorithmic singularities. Computational aspects of the solutions are also considered in view of real-time implementation of a kinematic control algorithm. The method is applied to a seven-degree-of-freedom manipulator in numerical case studies to demonstrate its effectiveness.

Force/position control strategies provide an effective framework to deal with tasks involving interaction with the environment. In this paper the parallel approach to force/position control of robotic manipulators is presented. It shows a complete use of the available sensor measurements by operating the control action in a full-dimensional space without using selection matrices. Conflicting situations between the position and force tasks are managed using a priority strategy: the force control loop is designed to prevail over the position control loop. This choice ensures limited deviations from the prescribed force trajectory in every situation, guaranteeing automatic recovery from unplanned collisions. A dynamic force/position parallel control law is presented and its performance in presence of an elastic environment is analyzed; simplification of the dynamic control law is also discussed leading to a PID-type parallel controller. Two case studies are worked out that show the effectiveness of the approach in application to an industrial robot.>

The manipulability ellipsoids are used in robotics as a measure of manipulators' performances achievable during task execution. The definition of these geometrical entities is based on the Jacobian of the manipulator, and the physical meaning given to the ellipsoids is related to the capability of the mechanism to apply forces with the end effector or to move the tool in some directions of the task-space. P. Chiacchio et al. (ibid., vol.7, p.678-685, 1991) have extended this concept to the case of cooperating manipulators. Nevertheless, some questions are still open, both with respect to the basic definition and use of manipulability ellipsoids. The commenter shows by simple examples that the use of manipulability ellipsoids for multiarm systems gives misleading results, and he disagrees with the above authors' definition of ellipsoids. The authors defend their work.>

Three schemes are developed which are aimed at achieving cooperative control of multiple arm systems manipulating a common object. The first scheme operates wholly on the object task space variables. The second scheme operates on the joint space variables that can be derived via a kinematic inversion from the cooperative task space variables. The third scheme combines the features of the two by solving the cooperation at the inverse kinematic level and acting the control at the object level. Simulation results are provided for a two-arm planar system to investigate the behavior of the controlled system in the case of inaccurate object modeling.>

Singularity robust redundancy resolution with task priority can be implemented using the extended Jacobian technique with weighted damped least-squares. The resulting scheme is simple to implement and involves less computation than the task priority scheme. The minimum singular value of the Jacobian can be estimated reliably and accurately with little computation, and this estimate was used to calculate an appropriate damping factor. A constant damping factor was also used with good results. The scheme was successfully implemented in a simulation study with a seven-joint manipulator with a kinematic design derived from the PUMA geometry.>

New definitions of force and velocity manipulability ellipsoids for multiple-arm systems are given. A suitable kinetostatic formulation for multiple cooperating arms is adopted that allows a global task space description of external and internal forces as well as absolute and relative velocities at the object level. The concept of a force manipulability ellipsoid for a single arm is formally extended to the multi-arm case by regarding the whole system as a mechanical transformer from the extended joint space to the global task space. Kinetostatic duality properties are then exploited to derive velocity manipulability ellipsoids for the multiple-arm system. The proposed method is compared with other approaches using numerical examples.>

A solution to the problem of singularities for six-joint manipulators is presented. By using this method, the unachievable components of the commanded motion are removed, while an exact inverse kinematic solution is used for the remaining motion components. At a singularity there are directions in Cartesian space where a differential translation or rotation cannot be specified. The underlying area is to identify these directions and then to eliminate the corresponding components of the commanded motion when the manipulator becomes singular using a pseudoinverse of the manipulator Jacobian. In order to avoid excessive joint velocities close to the singularities, the manipulator is treated as singular in the neighborhood of the singularity. A continuous solution is achieved by interpolation in the degenerate directions.>