This paper presents a method of designing variable structure control systems for robots. As the on-board robot computational resources are limited, but in some cases the demands imposed on the robot by the user are virtually limitless, the solution is to produce a variable structure system. The task dependent part has to be exchanged, however the task governs the activities of the robot. Thus not only exchange of some task-dependent modules is required, but also supervisory responsibilities have to be switched. Such control systems are necessary in the case of robot companions, where the owner of the robot may demand from it to

PurposeThis 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.Design/methodology/approachThe 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.FindingsThe 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.Research limitations/implicationsThe 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.Practical implicationsThe MRROC++ robot programming framework can be applied to the implementation of diverse robot controllers executing complex service tasks.Originality/valueA 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.

Purpose: 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. Design/methodology/approach: 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. Findings: 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. Originality/value: 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.

An application of advanced optimization techniques to solve the path planning problem for closed chain robot systems is proposed. The approach to path planning is formulated as a "quasi-dynamic" NonLinear Programming (NLP) problem with equality and inequality constraints in terms of the joint variables. The essence of the method is to find joint paths which satisfy the given constraints and minimize the proposed performance index. For numerical solution of the NLP problem, the IPOPT solver is used, which implements a nonlinear primal-dual interior-point method, one of the leading techniques for large-scale nonlinear optimization.

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The paper describes a prototype robot which due to its serial‐parallel structure exhibits, high stiffness and has a large work envelope. These features make this robot suitable for relatively high precision machining operations on large workpieces. The conroller for this robot was based on MRROC++, which is a robot programming framework. Thus the controller could be tailored to the tasks at hand, including the capability of in‐program switching of kinematic model parameters. To obtain those parameters for different locations in the work‐space a calibration procedure using linear measurement guides has been devised.

The paper1 concentrates on the way that the MRROC++ robot programming framework has been applied to produce control systems for robots of different types performing diverse tasks. Moreover, both a brTief formal specification and the method of implementation of the MRROC++ based systems is presented.

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