Search results

This paper seeks to develop universal software (a programming framework) enabling the implementation of service robot controllers. The software should distinguish the hardware‐oriented part of the system from the task‐oriented one. Moreover, force, vision as well as other sensors should be taken into account. Multi‐effector systems have to be considered.

The robot programming framework MRROC++ has been implemented as a hierarchical structure composed of processes, potentially consisting of threads. All of the software is written in an object‐oriented manner using C++ and is supervised by a QNX real‐time operating system. The framework has been verified on several systems executing diverse tasks. Here, a Rubik's cube puzzle‐solving system, consisting of two arms and utilizing force control and visual servos, is presented.

The presented framework is well suited to tasks requiring two‐handed manipulation with force sensing, visual servoing and online construction of plans of actions. The Rubik's cube puzzle is a reasonable initial benchmark for validation of fundamental service robot capabilities. It requires force sensing and sight coupled with two‐handed manipulation and logical reasoning, as do the majority of service tasks. Owing to the use of force sensing during manipulation, jamming of the faces has always been avoided; however, visual servoing could only cope with slow handing over of the cube due to the volume of computations associated with vision processing.

The proposed software structure does not limit the implementation of service robot controllers. However, some of the specific algorithms used for the solution of the benchmark task (i.e. Rubik's cube puzzle) need to be less time‐consuming.

The MRROC++ robot programming framework can be applied to the implementation of diverse robot controllers executing complex service tasks.

A demanding benchmark task for service robots has been formulated. This task, as well as many others, has been used to validate the MRROC++ robot programming framework which significantly facilitates the implementation of diverse robot systems.

Machining fixtures must fit exactly the work piece to support it appropriately. Even slight change in the design of the work piece renders the costly fixture useless. Substitution of traditional fixtures by a programmable multi‐robot system supporting the work pieces requires a specific control system and a specific programming method enabling its quick reconfiguration. The purpose of this paper is to develop a novel approach to task planning (programming) of the reconfigurable fixture system.

The multi‐robot control system has been designed following a formal approach based on the definition of the system structure in terms of agents and transition function definition of their behaviour. Thus, a modular system resulted, enabling software parameterisation. This facilitated the introduction of changes brought about by testing different variants of the mechanical structure of the system. A novel approach to task planning (programming) of the reconfigurable fixture system has been developed. Its solution is based on constraint satisfaction problem approach. The planner takes into account physical, geometrical, and time‐related constraints.

Reconfigurable fixture programming is performed by supplying CAD definition of the work piece. Out of this data the positions of the robots and the locations of the supporting heads are automatically generated. This proved to be an effective programming method. The control system on the basis of the thus obtained plan effectively controls the behaviours of the supporting robots in both drilling and milling operations.

The shop‐floor experiments with the system showed that the work piece is held stiffly enough for both milling and drilling operations performed by the CNC machine. If the number of diverse work piece shapes is large, the reconfigurable fixture is a cost‐effective alternative to the necessary multitude of traditional fixtures. Moreover, the proposed design approach enables the control system to handle a variable number of controlled robots and accommodates possible changes to the hardware of the work piece supporting robots.

The use of thin sheets with 3D geometries is growing in quantity, due to current progress towards life‐cycle design and sustainable production, and growing in geometrical complexity, due to aesthetic and quality concerns. The growth in manufacturing equipment flexibility has not kept pace with these trends. The purpose of this paper is to propose a new reconfigurable fixture to shorten this gap.

The design implements a novel concept of fixturing. Without interrupting the machining process, a swarm of adaptable mobile agents periodically reposition and reconfigure to support the thin‐sheet workpiece near the tool‐point. The technology has been developed by adopting a multi‐disciplinary, life‐cycle approach. Modularity and eco‐sustainability paradigms have informed the design.

The performance of the physical prototype in an industrial scenario is highly satisfactory. Experiments demonstrate the ability of the system to reconfigure while maintaining machining accuracy in scenarios typical for aircraft part production.

Coordination between the machine‐tool numerical control and the fixture control is not complete and its improvement will make the manufacturing process more robust and autonomous.

The system allows reduction of shop‐floor fixturing inventory. Compared to other reconfigurable fixtures, SwarmItFIX is smarter, more flexible, lighter, and offers shorter reconfiguration times, easier set‐up, and better adaptability to a wider range of workpiece shapes.

This is a breakthrough idea, answering the challenges of hyper‐flexible manufacturing and the proliferation of thin‐sheet use. It is of significant value to mass‐customized industry and of special significance for small‐series production.

The application of thermal barrier coatings (TBCs) allows aero-engine blades to operate at higher temperatures with higher efficiency. The preparation of the TBCs increases the surface roughness of the blade, which impacts the thermal cycle life and thermal insulation performance of the coating. To reduce the surface roughness of blades, particularly the blades with small size and complex curvature, this paper aims to propose a method for industrial robot polishing trajectory planning based on on-site measuring point cloud.

The authors propose an integrated robotic polishing trajectory planning method using point cloud processing technical. At first, the acquired point cloud is preprocessed, which includes filtering and plane segmentation algorithm, to extract the blade body point cloud. Then, the point cloud slicing algorithm and the intersection method are used to create a preliminary contact point set. Finally, the Douglas–Peucker algorithm and pose frame estimation are applied to extract the tool-tip positions and optimize the tool contact posture, respectively. The resultant trajectory is evaluated by simulation and experiment implementation.

The target points of trajectory are not evenly distributed on the blade surface but rather fluctuate with surface curvature. The simulated linear and orientation speeds of the robot end could be relatively steady over 98% of the total time within 20% reduction of the rest time. After polishing experiments, the coating roughness on the blade surface is reduced dramatically from Ra 7–8 µm to below Ra 1.0 µm. The removal of the TBCs is less than 100 mg, which is significantly less than the weight of the prepared coatings. The blade surface becomes smoothed to a mirror-like state.

The research on robotic polishing of aero-engine turbine blade TBCs is worthwhile. The real-time trajectory planning based on measuring point cloud can address the problem that there is no standard computer-aided drawing model and the geometry and size of the workpiece to be processed differ. The extraction and optimization of tool contact points based on point cloud features can enhance the smoothness of the robot movement, stability of the polishing speed and performance of the blade surface after polishing.

The purpose of this paper is to generate grinding trajectory of unknown model parts simply and efficiently. In this paper, a method of grinding trajectory generation of hybrid robot based on Cartesian space direct teaching technology is proposed.

This method first realizes the direct teaching of hybrid robot based on 3Dconnexion SpaceMouse (3DMouse) sensor, and the full path points of the robot are recorded in the teaching process. To reduce the jitter and make the speed control more freely when dragging the robot, the sensor data is processed by Kalman filter, and a variable admittance control model is established. And the joint constraint processing is given during teaching. After that, the path points are modified and fitted into double B-splines, and the speed planning is performed to generate the final grinding trajectory.

Experiment verifies the feasibility of using direct teaching technology in Cartesian space to generate grinding trajectory of unknown model parts. By fitting all the teaching points into cubic B-spline, the smoothness of the grinding trajectory is improved.

The whole method is verified by the self-developed TriMule-600 hybrid robot, and it can also be applied to other industrial robots.

The main contribution of this paper is to realize the direct teaching and trajectory generation of the hybrid robot in Cartesian space, which provides an effective new method for the robot to generate grinding trajectory of unknown model parts.