Recently, 3D printing has become one of the most popular additive manufacturing technologies. This technology has been utilised to prototype trial and produced components for various applications, such as fashion, food, automotive, medical, and construction. In recent years, automation also has become increasingly prevalent in the construction field. Extrusion printing is the most successful method to print cementitious materials, but it still faces significant challenges, such as pumpability of materials, buildability, consistency in the materials, flowability, and workability. This paper investigates the properties of 3D printed fibre-reinforced cementitious mortar prisms and members in conjunction with automation to achieve the optimum mechanical strength of printed mortar and to obtain suitable flowability and consistent workability for the mixed cementitious mortar during the printing process. This study also considered the necessary trial tests, which are required to check the mechanical properties and behaviour of the proportions of the cementitious mix. Mechanical strength was measured and shown to increase when the samples were printed using fibre-reinforced mortar by means of a caulking gun, compared with the samples that were printed using the same mix delivered by a progressive cavity pump to a 6 degree-of-freedom robot. The flexural strength of the four-printed layer fibre-reinforced mortar was found to be 3.44 ± 0.11 MPa and 5.78 ± 0.02 MPa for the one-layer. Moreover, the mortar with different types of nozzles by means of caulking is printed and compared. Several experimental tests for the fresh state of the mortar were conducted and are discussed.

Additive manufacturing is a fabrication technology that is rapidly revolutionizing the manufacturing and construction sectors. In this paper, a review of various prototyping technologies for printing cementitious materials and selected 3D printing techniques are presented in detail. Benchmark examples are provided to compare three well-known printing techniques; inkjet printing (binder jetting), selected laser sintering (SLS), and extrusion printing (extrusion based process). A comprehensive search in the literature was conducted to identify various mix designs that could be employed when printing cementitious materials. Aspects of concrete mix design are described, and some new experiments are conducted to analyse the printability of new mixes by the authors. Future research in the area of the rheology of cementitious materials and its relationship with the structural performance of finished concretes are highlighted.

Deformable Linear Object (DLO) manipulation has wide application in industry and in daily life. Conventionally, it is difficult for a robot to manipulate a DLO to achieve the target configuration due to the absence of the universal model that specifies the DLO regardless of the material and environment. Since the state variable of a DLO can be very high dimensional, identifying such a model may require a huge number of samples. Thus, model-based planning of DLO manipulation would be impractical and unreasonable. In this paper, we explore another approach based on reinforcement learning. To this end, our approach is to apply a sample-efficient model-based reinforcement learning method, so-called PILCO [1], to resolve the high dimensional planning problem of DLO manipulation with a reasonable number of samples. To investigate the effectiveness of our approach, we developed an experimental setup with a dual-arm industrial robot and multiple sensors. Then, we conducted experiments to show that our approach is efficient by performing a DLO manipulation task.

This paper presents Game Adaptive Virtual Reality Rehabilitation (GAVRe ² ), a framework to augment upper limb rehabilitation using Virtual Reality (VR) gamification and haptic robotic manipulator feedback. GAVRe ² integrates independent systems in a modular fashion, connecting patients with therapists remotely to increase patient engagement during rehabilitation. GAVRe ² exploits VR capabilities to not only increase the productivity of therapists administering rehabilitation, but also to improve rehabilitation mobility for patients. Conventional rehabilitation requires face-to-face physical interactions in a clinical setting which can be inconvenient for patients. The GAVRe ² approach provides an avenue for rehabilitation in a domestic setting by remotely customizing a routine for the patient. Results are then reported back to therapists for data analysis and future training regime development. GAVRe ² is evaluated experimentally through a system that integrates a popular VR system, a RGB-D camera, and a collaborative industrial robot, with results indicating potential benefits for long-term rehabilitation and the opportunity for upper limb rehabilitation in a domestic setting.

This paper presents an approach for exploring a complex 3D environment with a sensor mounted on the end effector of a robot manipulator. In contrast to many current approaches which plan as far ahead as possible using as much environment information as is available, our approach considers only a small set of poses (vector of joint angles) neighbouring the robot's current pose in configuration space. Our approach is compared to an existing exploration strategy for a similar robot. Our results demonstrate a significant decrease in the number of information gain estimation calculations that need to be performed, while still gathering an equivalent or increased amount of information about the environment.