In this paper, we present a Mobile Agile Printer (MAP) construction robot; a highly agile, 4-legged, omnidirectional robot capable of 3D printing large structures. To overcome dynamic challenges when operating within an outdoors construction site, MAP incorporates a high-DoF 3D printing system connected to a mobile platform with novel features designed to enable disturbance rejection and live adaption to the robot's pose. In doing so, we demonstrate the benefits of designing construction robots with a focus on agility, a compact working volume and ability to operate within a potentially unlimited workspace. Performance tests were conducted showing smooth omni-directional motion as a key requirement for maintaining low 3D printing trajectory deviations over a large volume. In doing so, we show that MAP has the ability to construct in new ways more sensitive to its environment, context and concurrent on-site operations.

Supervising and controlling remote robot systems currently requires many specialised operators to have knowledge of the internal state of the system in addition to the environment. For applications such as remote maintenance of future nuclear fusion reactors, the number of robots (and hence supervisors) required to maintain or decommission a facility is too large to be financially feasible. To address this issue, this work explores the idea of intelligently filtering information so that a single user can supervise multiple robots safely. We gathered feedback from participants using five methods for teleoperating a semi-autonomous multi-robot system via Virtual Reality (VR). We present a novel 3D interaction method to filter the displayed information to allow the user to read information from the environment without being overwhelmed. The novelty of the interface design is the link between Semantic and Spatial filtering and the hierarchical information contained within the multi robot system. We conducted a user study including a cohort of expert robot teleoperators comparing these methods; highlighting the significant effects of 3D interface design on the performance and perceived workload of a user teleoperating many robot agents in complex environments. The results from this experiment and subjective user feedback will inform future investigations that build upon this initial work.

Remote inspection of a complex environment is a difficult, time consuming task for human operators to perform. The need to manually avoid obstacles whilst considering other performance factors i.e. time taken, joint effort and information gained represents significant challenges to continuous operation. This paper proposes an autonomous robotic solution for exploration of an unknown, complex environment using a high DoF robot arm with an eye in hand depth sensor. The main contribution of this work is a new strategy to find the next best view by evaluating frontier regions of the map to maximise coverage, in contrast to many current approaches which densely sample joint or workspace configurations of the robot. Multiple utility functions were evaluated that showed different behaviours. Our results indicated that the presented algorithm can explore an arbitrary environment efficiently while optimising various performance criteria based on the utility function chosen, application constraints and the desires of the user.