This paper introduces a novel NMPC formulation for real-time obstacle avoidance on heavy equipment by modeling both vehicle and obstacles as convex superellipsoids. The combination of this approach with the separating hyperplane theorem and Optimization Engine (OpEn) allows to achieve efficient obstacle avoidance in autonomous heavy equipment and robotics. We demonstrate the efficacy of the approach through simulated and experimental results, showcasing a skid-steer loader's capability to navigate in obstructed environments.

This paper investigates a single day event intended to encourage school students to take up STEM subjects from an early age, in order to access STEM fields later in their educational cycle and thus careers. The event was hosted at Queen’s University Belfast in conjunction with the QUB iAMS group and the IEEE. Teaching theories such as Bloom’s Taxonomy and constructivism, including social constructivism and constructionism, were used to optimize student learning. The students were given a number of tasks based on these theories and asked to rate them at the end. There was an overwhelmingly positive response from most students, both observed and in ratings. For each activity, the more learning theories applied, the better it was rated. Based on the results, the day was branded a success and will no doubt have a positive effect on encouraging pre-GCSE students to take up STEM subjects and fields.

The growing number of collaborative robotics in unstructured environments creates highly nonconvex nonlinear shared dynamical systems. For safety and speed, path planning and collision avoidance are of the utmost importance in these situations. We present a novel nonlinear MPC solution for use on a three-dimensional four-axis robotic manipulator. The system is the first of it's kind to take into account moving obstacles. Using the OpEn framework, optimisation is done by the PANOC and ALM techniques. Experimentation demonstrates extremely fast solver times on both PC and embedded platforms.

The Baxter robot by ReThink Robotics is a dual arm collaborative platform, which can perform multiple tasks and is designed for use in an unstructured environment. Such robotic manipulators working in tandem have certain advantages over single arms when manipulating heavy or large, awkwardly shaped objects. With the attachment of two custom 3D -printed end-effectors, the robot gains the ability to push and hold objects of this kind. This paper deals with the preliminary steps in creating a reliable controller feedback signal using the robot's on-board torque and positioning sensors. Determining the best joint signal and designing a suitable filter are two challenges that are addressed. The paper concludes that the torque values from the centre wrist joint undergo the largest increase in value caused by vibrations during slip. A filtering array technique is also proposed, successfully removing unwanted noise from the torque signal, allowing slip events to be effectively isolated. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

When dealing with robotic manipulation tasks, slip detection and control is vital to overcome payload uncertainties and to compensate for external disturbances. Many modern smart manipulators are shipped with integrated joint torque sensing capabilities providing a potential means of detecting slip and hence generating a feedback signal for slip control, without the need for additional external sensors. This paper investigates preliminary results on slip detection with an aim to extend the existing work on single manipulator to a dual arm cooperative manipulator system. The slip signal is obtained through filtering of onboard joint torque measurements when different materials are held in a friction grip between the two cooperating robotic end-effectors of a Baxter robot.