A Rapidly Reconfigurable Robotics Workcell and Its Applictions for Tissue Engineering

This article describes the development of a component-based technology robot system that can be rapidly configured to perform a specific manufacturing task. The system is conceived with standard and inter-operable components including actuator modules, rigid link connectors and tools that can be assembled into robots with arbitrary geometry and degrees of freedom. The reconfigurable "plug-and-play" robot kinematic and dynamic modeling algorithms are developed. These algorithms are the basis for the control and simulation of reconfigurable robots. The concept of robot configuration optimization is introduced for the effective use of the rapidly reconfigurable robots. Control and communications of the workcell components are facilitated by a workcell-wide TCP/IP network and device level CAN-bus networks. An object-oriented simulation and visualization software for the reconfigurable robot is developed based on Windows NT. Prototypes of the robot systems configured to perform 3D contour following task and the positioning task are constructed and demonstrated. Applications of such systems for biomedical tissue scaffold fabrication are considered.Singapore-MIT Alliance (SMA

Software architecture for a distributed real-time system in Ada, with application to telerobotics

The architecture structure and software design methodology presented is described in the context of telerobotic application in Ada, specifically the Engineering Test Bed (ETB), which was developed to support the Flight Telerobotic Servicer (FTS) Program at GSFC. However, the nature of the architecture is such that it has applications to any multiprocessor distributed real-time system. The ETB architecture, which is a derivation of the NASA/NBS Standard Reference Model (NASREM), defines a hierarchy for representing a telerobot system. Within this hierarchy, a module is a logical entity consisting of the software associated with a set of related hardware components in the robot system. A module is comprised of submodules, which are cyclically executing processes that each perform a specific set of functions. The submodules in a module can run on separate processors. The submodules in the system communicate via command/status (C/S) interface channels, which are used to send commands down and relay status back up the system hierarchy. Submodules also communicate via setpoint data links, which are used to transfer control data from one submodule to another. A submodule invokes submodule algorithms (SMA's) to perform algorithmic operations. Data that describe or models a physical component of the system are stored as objects in the World Model (WM). The WM is a system-wide distributed database that is accessible to submodules in all modules of the system for creating, reading, and writing objects

BrainFrame: A node-level heterogeneous accelerator platform for neuron simulations

Objective: The advent of High-Performance Computing (HPC) in recent years has led to its increasing use in brain study through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the vast diversity of the modeling field does not permit for a single acceleration (or homogeneous) platform to effectively address the complete array of modeling requirements. Approach: In this paper we propose and build BrainFrame, a heterogeneous acceleration platform, incorporating three distinct acceleration technologies, a Dataflow Engine, a Xeon Phi and a GP-GPU. The PyNN framework is also integrated into the platform. As a challenging proof of concept, we analyze the performance of BrainFrame on different instances of a state-of-the-art neuron model, modeling the Inferior- Olivary Nucleus using a biophysically-meaningful, extended Hodgkin-Huxley representation. The model instances take into account not only the neuronal- network dimensions but also different network-connectivity circumstances that can drastically change application workload characteristics. Main results: The synthetic approach of three HPC technologies demonstrated that BrainFrame is better able to cope with the modeling diversity encountered. Our performance analysis shows clearly that the model directly affect performance and all three technologies are required to cope with all the model use cases.Comment: 16 pages, 18 figures, 5 table

A 17 degree of freedom anthropomorphic manipulator

A 17 axis anthropomorphic manipulator, providing coordinated control of two seven degree of freedom arms mounted on a three degree of freedom torso-waist assembly, is presented. This massively redundant telerobot, designated the Robotics Research K/B-2017 Dexterous Manipulator, employs a modular mechanism design with joint-mounted actuators based on brushless motors and harmonic drive gear reducers. Direct joint torque control at the servo level causes these high-output joint drives to behave like direct-drive actuators, facilitating the implementation of an effective impedance control scheme. The redundant, but conservative motion control system models the manipulator as a spring-loaded linkage with viscous damping and rotary inertia at each joint. This approach allows for real time, sensor-driven control of manipulator pose using a hierarchy of competing rules, or objective functions, to avoid unplanned collisions with objects in the workplace, to produce energy-efficient, graceful motion, to increase leverage, to control effective impedance at the tool or to favor overloaded joints

Reconfigurable Computing Applied to Latency Reduction for the Tactile Internet

Tactile internet applications allow robotic devices to be remotely controlled over a communication medium with an unnoticeable time delay. In a bilateral communication, the acceptable round trip latency is usually in the order of 1ms up to 10ms depending on the application requirements. It is estimated that 70% of the total latency is generated by the communication network, and the remaining 30% is produced by master and slave devices. Thus, this paper aims to propose a strategy to reduce 30% of the total latency that is produced by such devices. The strategy is to apply reconfigurable computation using FPGAs to minimize the execution time of device-associated algorithms. With this in mind, this work presents a hardware reference model for modules that implement nonlinear positioning and force calculations as well as a tactile system formed by two robotic manipulators. In addition to presenting the implementation details, simulations and experimental tests are performed in order to validate the proposed model. Results associated with the FPGA sampling rate, throughput, latency, and post-synthesis occupancy area are analyzed.Comment: 20 pages, 32 Figure

Inverse kinematics problem in robotics using neural networks

In this paper, Multilayer Feedforward Networks are applied to the robot inverse kinematic problem. The networks are trained with endeffector position and joint angles. After training, performance is measured by having the network generate joint angles for arbitrary endeffector trajectories. A 3-degree-of-freedom (DOF) spatial manipulator is used for the study. It is found that neural networks provide a simple and effective way to both model the manipulator inverse kinematics and circumvent the problems associated with algorithmic solution methods

Motion Control of the Hybrid Wheeled-Legged Quadruped Robot Centauro

Emerging applications will demand robots to deal with a complex environment, which lacks the structure and predictability of the industrial workspace. Complex scenarios will require robot complexity to increase as well, as compared to classical topologies such as fixed-base manipulators, wheeled mobile platforms, tracked vehicles, and their combinations. Legged robots, such as humanoids and quadrupeds, promise to provide platforms which are flexible enough to handle real world scenarios; however, the improved flexibility comes at the cost of way higher control complexity. As a trade-off, hybrid wheeled-legged robots have been proposed, resulting in the mitigation of control complexity whenever the ground surface is suitable for driving. Following this idea, a new hybrid robot called Centauro has been developed inside the Humanoid and Human Centered Mechatronics lab at Istituto Italiano di Tecnologia (IIT). Centauro is a wheeled-legged quadruped with a humanoid bi-manual upper-body. Differently from other platform of similar concept, Centauro employs customized actuation units, which provide high torque outputs, moderately fast motions, and the possibility to control the exerted torque. Moreover, with more than forty motors moving its limbs, Centauro is a very redundant platform, with the potential to execute many different tasks at the same time. This thesis deals with the design and development of a software architecture, and a control system, tailored to such a robot; both wheeled and legged locomotion strategies have been studied, as well as prioritized, whole-body and interaction controllers exploiting the robot torque control capabilities, and capable to handle the system redundancy. A novel software architecture, made of (i) a real-time robotic middleware, and (ii) a framework for online, prioritized Cartesian controller, forms the basis of the entire work