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This paper seeks to present an acceleration‐based force‐impedance controller, applied to a six‐dof parallel mini‐manipulator: the robotic controlled impedance device (RCID).

The proposed control strategy involves three cascade controllers: an inner acceleration controller, built as a set of six single input/single output acceleration controllers (one per manipulator axis), an impedance task‐space controller, and an outer force controller.

The control strategy enables two kinds of manipulator behaviour: force‐limited impedance control and position‐limited force control. The type of behaviour depends only on the chosen manipulator trajectories.

The RCID may be used as a force‐impedance controlled auxiliary device, coupled in series with a position‐controlled commercial industrial robot. The two manipulators combined behave as a single manipulator, having the impedance and force control performance of the RCID, as well as the workspace and trajectory tracking performance of the industrial manipulator. The industrial manipulator should perform free space motion trajectory tracking, the RCID being kept in a “home” position, preserving its small workspace for impedance and force control.

A robust control strategy that enables good performance, while the robot executes tasks that involve interaction with the environment, is being proposed. Experimental results on a force‐impedance controlled six‐dof parallel mini‐manipulator are presented.

The purpose of this paper is to present experience from a real‐world demonstration of autonomous industrial mobile manipulation (AIMM) based on the mobile manipulator “Little Helper” performing multiple part feeding at the pump manufacturer Grundfos A/S.

The necessary AIMM technologies exist at a mature level – the reason that no mobile manipulators have yet been implemented in industrial environments, is that research in the right applications have not been carried out. The paper proposes a pragmatic approach consisting of: a commercial‐off‐the‐shelf (COTS) mobile manipulator system design (“Little Helper”), a suitable and comprehensive industrial application (multiple part feeding), and a general implementation concept for industrial environments (the “Bartender Concept”).

Results from the three days of real‐world demonstration show that “Little Helper” is capable of successfully servicing four part feeders in three production cells using command signals from an Open Process Control (OPC) server. Furthermore, the paper presents future research and development suggestions for AIMM, which contributes to near‐term industrial maturation and implementation.

The paper presents a full‐scale demonstration of a state‐of‐the‐art COTS autonomous mobile manipulator system with particular focus on industrial utilization and application.

In the paper is presented the practical application of the manipulator automatic two‐level control concept. Anthropomorphic configuration of the system was chosen, consisting of the minimal configuration, which solves the task of attaining the position and the gripper, which has to satisfy correct orientation in approaching the working object, as well as manipulation of the same. The manipulator configuration, chosen in that way, was applied to the concrete task of final treatment of the thermostatic element for the automobile industry. Realization project of this system contains three basic elements:

Streamlining automated processes is currently undertaken by developing optimization methods and algorithms for robotic manipulators. This paper aims to present a new approach to improve streamlining of automatic processes. This new approach allows for multiple robotic manipulators commonly found in the industrial environment to handle different scenarios, thus providing a high-flexibility solution to automated processes.

The developed system is based on a spatial discretization methodology capable of describing the surrounding environment of the robot, followed by a novel path-planning algorithm. Gazebo was the simulation engine chosen, and the robotic manipulator used was the Universal Robot 5 (UR5). The proposed system was tested using the premises of two robotic challenges: EuRoC and Amazon Picking Challenge.

The developed system was able to identify and describe the influence of each joint in the Cartesian space, and it was possible to control multiple robotic manipulators safely regardless of any obstacles in a given scene.

This new system was tested in both real and simulated environments, and data collected showed that this new system performed well in real-life scenarios, such as EuRoC and Amazon Picking Challenge.

The new proposed approach can be valuable in the robotics field with applications in various industrial scenarios, as it provides a flexible solution for multiple robotic manipulator path and motion planning.

Manipulators are often subjected to joint flexibility caused by various causes in industrial applications, such as shaft windup, harmonic drives and bearing deformation. However, many industrial robots are only equipped with motor-side encoders because link-side encoders and torque transducers are expensive. Because of joint flexibility and resulted slow response rate, control performance of these manipulators is very limited. Based on this, the purpose of this paper is to use easy-to-install and cheap accelerometers to improve control performance of such manipulators.

First, a novel tip-acceleration feedback method is proposed to avoid amplifications of approximation errors caused by inversion of the Jacobian matrix. Then, a new control scheme, consisting an artificial neural network, a proportional-derivative (PD) controller and a reference model, is proposed to track motor-side position and suppress link-side vibration.

By using the proposed tip-acceleration feedback method, each link’s vibration can be suppressed correlatively. Through the networks, smaller motor-side tracking errors can be obtained and unknown dynamics can be compensated. Tracking and convergence performance of the network-based system can be improved by using the additional PD controller.

The originality is based on using accelerometers to improve link-side vibration suppression and control performance of flexible-joint manipulators. The previously used methods need expensive link-side sensors or accurate robot model, which is unavailable for many industrial robots only equipped with motor-side encoders. The report proposed a novel acceleration feedback method and used networks to solve such problems.

Safety is an important issue when manipulators operate in an environment where humans are present, such as the agriculture industry. An intrinsically safe mechanical system guarantees human safety when electronics or controls fail. However, industry also demands a certain operating velocity. A low inertia is the most important aspect to combine safety with a useful operating velocity, because this will limit the amount of kinetic or potential energy in the system and the required actuation forces. Low‐actuation forces limit the amount of static contact pressure between manipulator and human, a requirement for intrinsic safety. Low energy means that less contact force is required to put the manipulator to a stop in collision, an additional requirement. The goal of this paper is to find the maximum industrially applicable, manipulator mass for which intrinsic mechanical safety is guaranteed.

Observing existing and proposed manipulators in agriculture results in a required cycle time of 0.9 s, trajectory of 0.8 m and payload of 2 kg. Three important trade‐offs applying to the manipulator are identified. The first is between maximum velocity and acceleration, using cycle time and trajectory. The second is between maximum acceleration and mass, based on a measure for pain in contact pressure. The third is between maximum velocity and mass, using a collision model and the contact pressure during collision.

Combining all three trade‐offs results in an allowable arm effective inertia of 5.1 kg. Taking payload into account and converting to a realistic mass distribution results in a total mass of 9.3 kg. Compared to existing manipulators, both mass and payload are ambitious but realistic for the future development of an intrinsically safe manipulator.

Accuracy in positioning is not taken into account.

This paper combines safety criteria on maximum energy and maximum static pressure, while also taking industrial applicable operating velocity into account.

A method for the synthesis of dynamic control is presented. The method is based on an exact modelling of manipulator dynamics and a relatively simple synthesis of control algorithms. The authors have applied the method to a UMS‐2 industrial robot.

The purpose of this paper is to provide a review of the interdisciplinary research field, autonomous industrial mobile manipulation (AIMM), with an emphasis on physical implementations and applications.

Following an introduction to AIMM, this paper investigates the missing links and gaps between the research and developments efforts and the real‐world application requirements, in order to bring the AIMM technology from laboratories to manufacturing environments. The investigation is based on 12 general application requirements for robotics: sustainability, configuration, adaptation, autonomy, positioning, manipulation and grasping, robot‐robot interaction, human‐robot interaction, process quality, dependability, and physical properties.

The concise yet comprehensive review provides both researchers (academia) and practitioners (industry) with a quick and gentle overview of AIMM. Furthermore, the paper identifies key open issues and promising research directions to realize real‐world integration and maturation of the AIMM technology.

This paper reviews the interdisciplinary research field, autonomous industrial mobile manipulation (AIMM).

The purpose of this study has been to evaluate the technology of autonomous mobile manipulation in a real world industrial manufacturing environment. The objective has been to obtain experience in the integration with existing equipment and determine key challenges in maturing the technology to a level of readiness suitable for industry. Despite much research within the topic of industrial mobile manipulation, the technology has not yet found its way to the industry. To mature the technology to a level of readiness suitable for industry real-world experience is crucial. This paper reports from such a real-world industrial experiment with two mobile manipulators.

In the experiment, autonomous industrial mobile manipulators are integrated into the actual manufacturing environment of the pump manufacturer Grundfos. The two robots together solve the task of producing rotors; a task constituted by several sub-tasks ranging from logistics to complex assembly. With a total duration of 10 days, the experiment includes workspace adaptation, safety regulations, rapid robot instruction and running production.

With a setup time of less than one day, it was possible to program both robots to perform the production scenario in collaboration. Despite the success, the experiment clearly demonstrated several topics in need of further research before the technology can be made available to the industry: robustness and cycle time, safety investigations and possibly standardization, and robot and workstation re-configurability.

Despite the attention of research around the world, the topic of industrial mobile manipulation has only seen a limited number of real-world integrations. This work reports from a comprehensive integration into a real-world running production and thus reports on the key challenges identified from this integration.

The purpose of this paper is to review the progress made in arc welding automation using trajectory planning, seam tracking and control methodologies.

This paper discusses key issues in trajectory planning towards achieving full automation of arc welding robots. The identified issues in trajectory planning are real-time control, optimization methods, seam tracking and control methodologies. Recent research is considered and brief conclusions are drawn.

The major difficulty towards realizing a fully intelligent robotic arc welding system remains an optimal blend and good understanding of trajectory planning, seam tracking and advanced control methodologies. An intelligent trajectory tracking ability is strongly required in robotic arc welding, due to the positional errors caused by several disturbances that prevent the development of quality welds. An exciting prospect will be the creation of an effective hybrid optimization technique which is expected to lead to new scientific knowledge by combining robotic systems with artificial intelligence.

This paper illustrates the vital role played by optimization methods for trajectory design in arc robotic welding automation, especially the non-gradient approaches (those based on certain characteristics and behaviour of biological, molecular, swarm of insects and neurobiological systems). Effective trajectory planning techniques leading to real-time control and sensing systems leading to seam tracking have also been studied.