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Reconfigurability of the assembly fixtures, which enables a set of sheet metal automotive parts to be produced on a single production line, is becoming crucial to maintaining competitiveness in the rapidly changing market. One of the key issues in reconfigurable fixture design is to identify the fixture configuration and make sure there is enough workspace for a family of parts. The purpose of this paper is to address this issue, through the design and analysis of two novel reconfigurable fixturing robots.

Following an introduction, the application of the reconfigurable fixturing robot addressed in this paper is described; it is characterized by using parallel manipulator as programmable fixture elements. Kinematic design and reconfigurable design of the fixturing robot is presented based on screw theory and modularized design, respectively.

The proposed reconfigurable fixturing robots can transform their configurations with 4 DoF (degrees‐of‐freedom), and have a continuous workspace for their application.

Reconfigurability of the assembly fixtures is an important issue for automotive manufacturing, due to the highly competitive nature of this industry. The proposed reconfigurable fixturing robots can greatly facilitate the development of new models of vehicles.

The purpose of this paper is to propose a universal approach for configuration synthesis of reconfigurable robots based on fault tolerant indices.

A universal approach is introduced to determine the best configuration of redundant reconfigurable robots based on fault tolerant indices. For a given task, a method based on genetic algorithm for evaluation on the index, fault tolerant workspace reachability, is employed first to search the robot configurations with the fault tolerant ability for the desired task. Then, among the obtained robot configurations, a method based on gradient projection algorithm is adopted to further find out the robot configuration that has the comparatively best fault tolerant operation dexterity. The validity of this approach is proved by conducting computational simulations.

A universal approach has been found for configuration synthesis of reconfigurable robots based on fault tolerant indices.

The paper introduces a universal approach for configuration synthesis of reconfigurable robots to not only guarantee the robot with the synthesized configuration possesses the fault tolerant ability for the given task, but also has relatively high fault tolerant operation dexterity.

This paper aims to explain the design of a novel leg mechanism for SLEGS robot. SLEGS means both “S”-shaped for the legged robot and “O”-shaped for the wheeled robot. It is a reconfigurable/transformable mobile robot.

First, a novel robot leg is designed by inspiration from previous studies. Second, the SLEGS robot’s leg is modeled using 3D computer model, and kinematics analysis performed on the leg mechanism. Finally, the prototype of the novel leg was developed for the SLEGS robot.

The robot leg mechanism has both flexible and self-reconfigurable modular features. All legs automatically take the form of both a rotating wheel and a walking leg with a self-reconfigurable modular feature.

The modeled leg is original in terms of its novel locomotion mechanism in both the walking and wheeled configurations.

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 purpose of this paper is to introduce the design and the multi‐mode locomotion function of the new reconfigurable modular robotic system – UBot system – which combines the advantages from the chain‐based and lattice‐based self‐reconfigurable robots.

The UBot modules the authors have designed are based on the universal joint and of cubic shape with two rotational joints and reliable automatic connecting mechanism. The modules are compact and flexible enough for locomotion and reconfiguration. The system can move in different modes to satisfy different terrains, through changing the modules' local connections and rotation of modules' joints.

The UBot system can flexibly move in the modes of cross, loop, quadruped, snake‐type and other type of locomotion modes. All the locomotion has been implemented in the physical experiments.

The UBot module is the new reconfigurable module which has two joints in one unit of regular cubic space and four reliable automatic connecting surfaces. A group of the modules is able to change its connective configuration by changing their local connections and has functionality of the corresponding traditional robotic system. Since it can travel through terrains that may not be fully characterized ahead of time, the system can be used in a large variety of tasks, such as transportation, assembly, inspection and exploration.

The purpose of this paper is to describe a shape‐shifting robot with diverse configurations, named “AMOEBA‐I”, which has been developed for search and rescue operations. The accessibility of this robot to unstructured environment is efficiently enhanced by changing its configuration. So the shape and reconfiguration of the robot should be considered in AMOEBA‐I path planning to improve work ability of the robot in complex environment. The unique accessibility of AMOEBA‐I is thus fully displayed.

An auto‐adapted path‐planning method is presented for AMOEBA‐I by introducing the reconfigurable ability of the robot into the modified potential field method. The modified potential field method solves the local minimum problem and goal‐unreachable with nearby obstacles (GUWNO) effectively. A method of the shape‐shifting robot's passing through the narrow space is studied by combining the corner detection with the modified potential field method.

The ability of the robot to automatically change configuration to pass through a narrow space is proven through the experiment. Simulation results show that the robot can change its own configurations to perform auto‐adapted path planning corresponding to the environmental variation. Therefore, the proposed method can improve the probability of completing the path planning. As a result, this method will shorten the path length and complete the rescue operation more effectively.

The paper presents an effective auto‐adapted path‐planning method that integrates the reconfigurable ability of the robot into the modified potential field method in order to realize the auto‐adapted path planning.

The purpose of this study is to explore using real-observation quantum genetic algorithms (RQGAs) to evolve neural controllers that are capable of controlling a self-reconfigurable modular robot in an adaptive locomotion task.

Quantum-inspired genetic algorithms (QGAs) have shown their superiority against conventional genetic algorithms in numerous challenging applications in recent years. The authors have experimented with several QGAs variants and real-observation QGA achieved the best results in solving numerical optimization problems. The modular robot used in this study is a hybrid simulated robot; each module has two degrees of freedom and four connecting faces. The modular robot also possesses self-reconfiguration and self-mobile capabilities.

The authors have conducted several experiments using different robot configurations ranging from a single module configuration to test the self-mobile property to several disconnected modules configuration to examine self-reconfiguration, as well as snake, quadruped and rolling track configurations. The results demonstrate that the robot was able to perform self-reconfiguration and produce stable gaits in all test scenarios.

The artificial neural controllers evolved using the real-observation QGA were able to control the self-reconfigurable modular robot in the adaptive locomotion task efficiently.

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.

This paper aims to present a new method to analyze the robot’s obstacle negotiation based on the terramechanics, where the terrain physical parameters, the sinkage and the slippage of the robot are taken into account, to enhance the robot’s trafficability.

In this paper, terramechanics is used in motion planning for all-terrain obstacle negotiation. First, wheel/track-terrain interaction models are established and used to analyze traction performances in different locomotion modes of the reconfigurable robot. Next, several key steps of obstacle-climbing are reanalyzed and the sinkage, the slippage and the drawbar pull are obtained by the models in these steps. In addition, an obstacle negotiation analysis method on loose soil is proposed. Finally, experiments in different locomotion modes are conducted and the results demonstrate that the model is more suitable for practical applications than the center of gravity (CoG) kinematic model.

Using the traction performance experimental platform, the relationships between the drawbar pull and the slippage in different locomotion modes are obtained, and then the traction performances are obtained. The experimental results show that the relationships obtained by the models are in good agreement with the measured. The obstacle-climbing experiments are carried out to confirm the availability of the method, and the experimental results demonstrate that the model is more suitable for practical applications than the CoG kinematic model.

Comparing with the results without considering Terramechanics, obstacle-negotiation analysis based on the proposed track-terrain interaction model considering Terramechanics is much more accurate than without considering Terramechanics.