Keith Kershaw

A Multi-Sensor RSS Spatial Sensing-Based Robust Stochastic Optimization Algorithm for Enhanced Wireless Tethering

The reliability of wireless communication in a network of mobile wireless robot nodes depends on the received radio signal strength (RSS). When the robot nodes are deployed in hostile environments with ionizing radiations (such as in some scientific facilities), there is a possibility that some electronic components may fail randomly (due to radiation effects), which causes problems in wireless connectivity. The objective of this paper is to maximize robot mission capabilities by maximizing the wireless network capacity and to reduce the risk of communication failure. Thus, in this paper, we consider a multi-node wireless tethering structure called the “server-relay-client” framework that uses (multiple) relay nodes in between a server and a client node. We propose a robust stochastic optimization (RSO) algorithm using a multi-sensor-based RSS sampling method at the relay nodes to efficiently improve and balance the RSS between the source and client nodes to improve the network capacity and to provide redundant networking abilities. We use pre-processing techniques, such as exponential moving averaging and spatial averaging filters on the RSS data for smoothing. We apply a receiver spatial diversity concept and employ a position controller on the relay node using a stochastic gradient ascent method for self-positioning the relay node to achieve the RSS balancing task. The effectiveness of the proposed solution is validated by extensive simulations and field experiments in CERN facilities. For the field trials, we used a youBot mobile robot platform as the relay node, and two stand-alone Raspberry Pi computers as the client and server nodes. The algorithm has been proven to be robust to noise in the radio signals and to work effectively even under non-line-of-sight conditions.

Remote inspection, measurement and handling for LHC

Personnel access to the LHC tunnel will be restricted to varying extents during the life of the machine due to radiation, cryogenic and pressure hazards. The ability to carry out visual inspection, measurement and handling activities remotely during periods when the LHC tunnel is potentially hazardous offers advantages in terms of safety, accelerator down time, and costs. The first applications identified were remote measurement of radiation levels at the start of shut-down, remote geometrical survey measurements in the collimation regions, and remote visual inspection during pressure testing and initial machine cool-down. In addition, for remote handling operations, it will be necessary to be able to transmit several real-time video images from the tunnel to the control room. The paper describes the design, development and use of a remotely controlled vehicle to demonstrate the feasibility of meeting the above requirements in the LHC tunnel. Design choices are explained along with operating experience to-date and future development plans.

Experimental investigation of radio signal propagation in scientific facilities for telerobotic applications

Understanding the radio signal transmission characteristics in the environment where the telerobotic application is sought is a key part of achieving a reliable wireless communication link between a telerobot and a control station. In this paper, wireless communication requirements and a case study of a typical telerobotic application in an underground facility at CERN are presented. Then, the theoretical and experimental characteristics of radio propagation are investigated with respect to time, distance, location and surrounding objects. Based on analysis of the experimental findings, we show how a commercial wireless system, such as Wi-Fi, can be made suitable for a case study application at CERN.

Model Based On-Line Energy Prediction System for Semi-autonomous Mobile Robots

Maximizing energy autonomy is a consistent challenge when deploying mobile robots in ionizing radiation or other hazardous environments. Having a reliable robot system is essential for successful execution of missions and to avoid manual recovery of the robots in environments that are harmful to human beings. For deployment of robots missions at short notice, the ability to know beforehand the energy required for performing the task is essential. This paper presents a on-line method for predicting energy requirements based on the pre-determined power models for a mobile robot. A small mobile robot, Khepera III is used for the experimental study and the results are promising with high prediction accuracy. The applications of the energy prediction models in energy optimization and simulations are also discussed along with examples of significant energy savings.

Energy Management Module for Mobile Robots in Hostile Environments

In hostile environments at CERN and other similar scientific facilities, having a reliable mobile robot system is essential for successful execution of robotic missions and to avoid situations of manual recovery of the robots in the event that the robot runs out of energy. Because of environmental constraints, such mobile robots are usually battery-powered and hence energy management and optimization is one of the key challenges in this field. The ability to know beforehand the energy consumed by various elements of the robot (such as locomotion, sensors, controllers, computers and communication) will allow flexibility in planning or managing the tasks to be performed by the robot.

Spatial sampling methods for improved communication for wireless relay robots

Having reliable wireless communication in a network of mobile robots is an ongoing challenge, especially when the mobile robots are given tasks in hostile or harmful environments such as radiation environments in scientific facilities, tunnels with large metallic components and complicated geometries as found at CERN. In this paper, we propose a decentralised method for improving the wireless network throughput by optimizing the wireless relay robot position to receive the best wireless signal strength using implicit spatial diversity concepts and gradient-search algorithms. We experimentally demonstrate the effectiveness of the proposed solutions with a KUKA Youbot omni-directional mobile robot. The performance of the algorithms is compared under various scenarios in an underground scientific facility at CERN.

Remote Inspection, Measurement and Handling for Maintenance and Operation at CERN

Remote inspection, measurement and handling techniques are under development for use in CERNs particle accelerator facilities to reduce radiation exposure of personnel and reduce facility downtime when scheduled maintenance or breakdown repairs are needed. This paper gives an explanation of the potential benefits to CERN of remote inspection, measurement and handling along with a brief history of remote handling work at CERN. Recent projects are then described, covering the development work and operations forming part of CERNs recent remote inspection, measurement and handling activities.

Transport and installation of the LHC cryo-magnets

Eleven years have passed between the beginning of transport and handling studies in 1996 and the completion of the LHC cryo-magnets installation in 2007. More than 1700 heavy, long and fragile cryo-magnets had to be transported and installed in the 27 km long LHC tunnel with very restricted available space. The size and complexity of the project involved challenges in the field of equipment design and manufacturing, maintenance, training and follow-up of operators and logistics. The paper presents the milestones, problems to be overcome and lessons learned during this project.

A framework of teleoperated and stereo vision guided mobile manipulation for industrial automation

Smart and flexible manufacturing requests the adoption of industrial mobile manipulators in factory. The goal of autonomous mobile manipulation is the execution of complex manipulation tasks in unstructured and dynamic environments. It is significant that a mobile manipulator is able to detect and grasp the object in a fast and accurate manner. In this research, we developed a stereo vision system providing qualified point cloud data of the object. A modified and improved iterative closest point algorithm is applied to recognize the targeted object greatly avoiding the local minimum in template matching. Moreover, a stereo vision guided teleoperation control algorithm using virtual fixtures technology is adopted to enhance robot teaching ability. Combining these two functions, the mobile manipulator is able to learn semi-autonomously and work autonomously. The key components and the system performance are then tested and proved in both simulation and experiments.

Experimental modal analysis of components of the LHC experiments

Experimental modal analysis of components of the LHC experiments is performed with the purpose of determining their fundamental frequencies, their damping and the mode shapes of light and fragile detector components. This process permits to confirm or replace Finite Element analysis in the case of complex structures (with cables and substructure coupling). It helps solving structural mechanical problems to improve the operational stability and determine the acceleration specifications for transport operations. This paper describes the hardware and software equipment used to perform a modal analysis on particular structures such as a particle detector and the method of curve fitting to extract the results of the measurements. This paper exposes also the main results obtained for the LHC Experiments.