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Recent research has considered robotic machining as a dextrous alternative to traditional CNC machine tools for complex sculptured surfaces. One challenge in using robotic machining is that the stiffness is lower than traditional machine tools, due to the cantilever design of the links and low‐torsional stiffness of the actuators. This paper seeks to examine this limitation, using optimization algorithms to determine the best trajectories for the manipulators such that the stiffness is maximized.

The issue of low stiffness is addressed with an integrated off‐line planner and real‐time re‐planner. The available manipulator stiffness is maximized during off‐line planning through a trajectory resolution method that exploits the nullspace of the robot machining system. In response to unmodeled disturbances, a real‐time trajectory re‐planner utilizes a time‐scaling method to reduce the tool speed, thereby reducing the demand on the actuator torques, increasing the robot's dynamic stiffness capabilities. During real‐time re‐planning, priorities are assigned to conflicting performance criteria such as stiffness, collision avoidance, and joint limits.

The algorithms developed were able to generate trajectories with stiffer configurations, which resulted in a reduction in the actuator torques. The real‐time re‐planner successfully allowed the process plan to continue when disturbances were encountered.

Simulations are presented to demonstrate the effectiveness of the approach.

Addressing the limitation of stiffness in serial‐link manipulators will enable robots to become more suitable for machining tasks. The real‐time re‐planning approach will allow robots to become more autonomous during the execution of a given task.

An integrated off‐line and real‐time planning approach has been applied to robotic machining.

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.

States that manufacturing lines cannot be used for production during commissioning and that it is therefore always the goal to reduce the necessary efforts to a maximum extent. Starts with a description of the state‐of‐the‐art in this field based on the situation in the automotive industry. Additionally lists RTD fields to overcome these problems. Goes on to present methods and software tools aiming at a tremendous decrease in efforts required today.

The purpose of this paper is to determine the base position and the largest working area for mobile manipulators. The base position determines the workspace of the mobile manipulator, particularly when the operation mode is intermittent (i.e. the mobile platform stops when the manipulator conducts the task). When the base of the manipulator is in the intersection area of the Base’s Workable Location Spaces (BWLSes), the end effector (EE) can reach all path points. In this study, the intersection line of BWLSes is calculated numerically, and the largest working area is determined using the BWLS concept. The performance of this method is validated with simulations on specific surface segments, such as plane, cylinder and conical surface segments.

The BWLS is used to determine the largest working area and the base position in which the mobile manipulator can reach all path points with the objective of reducing off-line planning time.

Without considering the orientation of the EE, the base position and the working area for the mobile manipulator are determined using the BWLS. Compared to other methods, the proposed algorithm is beneficial when the planning problem has six dimensions, ensuring the reachability and stability of the EE.

The algorithm needs no manual configuration, and its performance is investigated for typical surfaces in practical applications.

Robotic friction stir welding (RFSW) is an innovative process which enables solid-state welding of aluminum parts using robots. A major drawback of this process is that the robot joints undergo elastic deformation during the welding, because of the high forces induced by the process. This leads to tool deviation and incorrect orientation. There is currently no computer-aided manufacturing/computer-aided design (CAD) software for generating off-line paths which integrates robot deflections, and the main purpose of this study is to propose an off-line methodology to plan a path for RFSW with the integration of the deflections.

The approach is divided into two steps. The first step consists of extracting position and orientation data from CAD models of the workpieces and adding the deflections calculated with a deflection model to generate a suitable path for performing RFSW. The second step consists of the smooth fitting of the suitable path using Bézier curves.

The method is experimentally validated by welding a curved workpiece using a Kuka KR500-2MT robot. A suitable tool position and orientation were calculated to perform this welding, an experimental procedure was set up, a defect-free weld was performed and a high accuracy was achieved in terms of position and orientation.

This method can help manufacturers to easily perform RFSW for three-dimensional workpieces regardless of the lateral tool deviation, loss of the right orientation and control force stability.

The originality of this method lies in compensating for robot deflections without using expensive sensors, which is the most commonly used method for compensating for robot deflection. This off-line method can lead to a reduction in programming time in comparison with teach programming method and leads to reduced investment costs in comparison with commercial off-line programming packages.

Planning robot cells, and proving and generating robot programs, can be swiftly and efficiently achieved with graphical simulation.

This paper presents the architecture of a system for robotic welding of complex tasks. The system integrates off‐line programming, control of redundant robots, collision‐free motion planning and sensor‐based control. An implementation for pipe structure welding made at Odense Steel Shipyard Ltd., Denmark, demonstrates the system can be used for automatic welding of complex products in one‐of‐a‐kind production.

Reports on an aggressive project to develop an advanced, automated welding system, being completed at Babcock & Wilcox, CIM Systems. This system, the programmable automated welding system (PAWS), involves the integration of both planning and control technologies to address the needs of small batch robotic welding operations. PAWS is specifically designed to provide an automated means of planning, controlling, and evaluating critical welding situations in shipyard environments to improve productivity and quality. Five varieties (wall, lathe, floor mount, cantilevered, and gantry) of PAWS welding systems currently exist.

The purpose of this paper is to focus on the local minima issue encountered in motion planning by the artificial potential field (APF) method, investigate the currently existing approaches and analyze four types of previous methods. Based on the conclusions of analysis, this paper presents an improved wall‐following approach for real‐time application in mobile robots.

In the proposed method, new switching conditions among various behaviors are reasonably designed in order to guarantee the reliability and the generality of the method. In addition, path memory is incorporated in this method to enhance the robot's cognition capability to the environment. Therefore, the new method greatly weakens the blindness of decision making of robot and it is very helpful to select appropriate behaviors facing to the changeable situation. Comparing with the previous methods which are normally considering specific obstacles, the effectiveness of this proposed method for the environment with convex polygon‐shaped obstacles has been theoretically proved. The simulation and experimental results further demonstrate that the proposed method is adaptable for the environment with convex polygon‐shaped obstacles or non‐convex polygon‐shaped obstacles. It has more widely generality and adaptiveness than other existed methods in complicated unknown environment.

The proposed method can effectively realize real time motion planning with high reliability and generality. The cognition capability of mobile robot to the environment can be improved in order to adapt to the changeable situation. The proposed method can be suitable to more complex unknown environment. It is more applicable for actual environment comparing with other traditional APF methods.

This paper has widely investigated the currently existed approaches and analyzes deeply on four types of traditional APF methods adopted for real time motion planning in unknown environment with simulation works. Based on the conclusions of analysis, this paper presents an improved wall‐following approach. The proposed method can realize real time motion planning considering more complex environment with high reliability and generality. The simulation and experimental results further demonstrate that the proposed method is adaptable for the environment with convex polygon‐shaped obstacles or non‐convex polygon‐shaped obstacles. It has more widely generality and adaptiveness than other existed methods in complicated unknown environment.

A minimum‐time path‐following algorithm for industrial robots is presented in this paper.

The algorithm generates off‐line a trajectory that, by exploiting knowledge of the dynamic model, takes into account the actuators' torque limits while preserving the geometric path.

The algorithm has been designed, implemented and extensively tested on a Comau SMART H4 robot, a closed‐chain six‐degree‐of‐freedom industrial manipulator.

The algorithm is currently part of the new generation of industrial controllers of the Comau robots, the C4G controller. It is a feature added as with the name SmartMove4.

The paper presents a new minimum‐time path‐following algorithm for industrial robots that, by exploiting knowledge of the dynamic model, takes into account the actuators' torque limits while preserving the geometric path.