Planning and Real Time Control of a Minimally Invasive Robotic Surgery System

This paper introduces the planning and control software of a teleoperating robotic system for minimally invasive surgery. It addresses the problem of how to organize a complex system with 41 degrees of freedom including robot setup planning, force feedback control and nullspace handling with three robotic arms. The planning software is separated into sequentially executed planning and registration procedures. An optimal setup is first planned in virtual reality and then adapted to variations in the operating room. The real time control system is composed of hierarchical layers. The design is flexible and expandable without losing performance. Structure, functionality and implementation of planning and control are described. The robotic system provides the surgeon with an intuitive hand-eye-coordination and force feedback in teleoperation for both hands

Modelling and analyzing adaptive self-assembling strategies with Maude

Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify, validate and analyse a prominent example of adaptive system: robot swarms equipped with self-assembly strategies. The analysis exploits the statistical model checker PVeStA

Engineering Method and Tool for the Complete Virtual Commissioning of Robotic Cells

Intelligent robotic manufacturing cells must adapt to ever-varying operating conditions, developing autonomously optimal manufacturing strategies to achieve the best quality and overall productivity. Intelligent and cognitive behaviors are realized by using distributed controllers, in which complex control logics must interact and process a wide variety of input/output signals. In particular, programmable logic controllers (PLCs) and robot controllers must be coordinated and integrated. Then, there is the need to simulate the robotic cells’ behavior for performance verification and optimization by evaluating the effects of both PLC and robot control codes. In this context, this work proposes a method, and its implementation into an integrated tool, to exploit the potential of ABB RobotStudio software as a virtual prototyping platform for robotic cells, in which real robots control codes are executed on a virtual controller and integrated with Beckhoff PLC environment. For this purpose, a PLC Smart Component was conceived as an extension of RobotStudio functionalities to exchange signals with a TwinCAT instance. The new module allows the virtual commissioning of a complete robotic cell to be performed, assessing the control logics effects on the overall productivity. The solution is demonstrated on a robotic assembly cell, showing its feasibility and effectiveness in optimizing the final performance

Modelling and analyzing adaptive self-assembling strategies with Maude

Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify, validate and analyse a prominent example of adaptive system: robot swarms equipped with self-assembly strategies. The analysis exploits the statistical model checker PVeStA

A Hardware-in-the-Loop Simulator for Software Development for a Mars Airplane

Draper Laboratory recently developed a Hardware-In-The-Loop Simulator (HILSIM) to provide a simulation of the Aerial Regional-scale Environmental Survey (ARES) airplane executing a mission in the Martian environment. The HILSIM was used to support risk mitigation activities under the Planetary Airplane Risk Reduction (PARR) program. PARR supported NASA Langley Research Center's (LaRC) ARES proposal efforts for the Mars Scout 2011 opportunity. The HILSIM software was a successful integration of two simulation frameworks, Draper's CSIM and NASA LaRC's Langley Standard Real-Time Simulation in C++ (LaSRS++)

Tools for Real-Time Control Systems Co-Design : A Survey

This report presents a survey of current simulation tools in the area of integrated control and real-time systems design. Each tool is presented with a quick overview followed by a more detailed section describing comparative aspects of the tool. These aspects describe the context and purpose of the tool (scenarios, development stages, activities, and qualities/constraints being addressed) and the actual tool technology (tool architecture, inputs, outputs, modeling content, extensibility and availability). The tools presented in the survey are the following; Jitterbug and TrueTime from the Department of Automatic Control at Lund University, Sweden, AIDA and XILO from the Department of Machine Design at the Royal Institute of Technology, Sweden, Ptolemy II from the Department of Electrical Engineering and Computer Sciences at Berkeley, California, RTSIM from the RETIS Laboratory, Pisa, Italy, and Syndex and Orccad from INRIA, France. The survey also briefly describes some existing commercial tools related to the area of real-time control systems

Software Abstractions for Simulation and Control of a Continuum Robot

Nordmann A, Rolf M, Wrede S. Software Abstractions for Simulation and Control of a Continuum Robot. In: SIMPAR2012 - SIMULATION, MODELING, and PROGRAMMING for AUTONOMOUS ROBOTS. 2012