Confined and cluttered aquatic environments present a number of significant challenges with respect to inspection by robotic platforms, including localisation and communications. Some of these can be mitigated by using collaborative heterogeneous multi-robot teams. An important element of such a system is collaborative control. This paper addresses this challenge by presenting an Image-Based Visual Servoing (IBVS), leader-follower control system for heterogeneous aquatic robots. Experiments were conducted in an uncluttered pond to demonstrate the capabilities of the system. The results show robots can maintain tracking each other with maximum$x$and$y$displacements of 0.42 m and 0.41 m, the maximum projection distance in the xy-plane of maintaining formation is 0.45 m, showing the stability and feasibility of deploying such system on underwater platforms.

The development of mobile robot platforms for inspection has gained traction in recent years. However, conventional mobile robots are unable to address the challenge of operating in extreme environments where the robot is required to traverse narrow gaps in highly cluttered areas with restricted access, typically through narrow ports. This article presents MIRRAX, a robot designed to meet these challenges by way of its reconfigurable capability. Controllers for the robot are detailed, along with an analysis on the controllability of the robot given the use of mecanum wheels in a variable configuration. Characterization on the robot's performance identified suitable configurations for operating in narrow environments. The experimental validation of the robot's controllability shows good agreement with the theoretical analysis and the capability to address the challenges of accessing entry ports as small as 150-mm diameter, as well as navigating through cluttered environments. This article also presents results from a deployment in a Magnox facility at the Sellafield nuclear site in the U.K.—the first robot to ever do so, for remote inspection and mapping.

Reconfigurable mobile robots are well suited for inspection tasks in legacy nuclear facilities where access is restricted and the environment is often cluttered. A reconfig-urable snake robot, MIRRAX, has previously been developed to investigate such facilities. The joints used for the robot's reconfiguration introduce additional constraints on the robot's control, such as balance, on top of the existing actuator and collision constraints. This paper presents a set-point controller for MIRRAX using vector-field inequalities to enforce hard constraints on the robot's balance, actuator limits, and collision avoidance in a single quadratic programming formulation. The controller has been evaluated in simulation and early experiments in some scenarios. The results show that the controller generates feasible control inputs that enable the robot to retain its balance while moving with less oscillation and operating within the actuation and collision constraints.

In recent years, the inspection of extreme environments using mobile robots has gained traction, as robots are able to mitigate the risk placed on humans and at times achieve what humans are unable to. In some scenarios, the robot is required to operate in cluttered environments with highly restricted access through 150 mm diameter ports. The MIRRAX robot has been designed to meet these challenges with the capability of reconfiguring itself to both access environments and navigate through tightly spaced obstacles. The joints used for reconfiguration of the robot introduce additional challenges for path planning due to the significant changes that can occur between adjacent poses. This paper presents a global path planner for MIRRAX. A Voronoi diagram is first used to generate a sparse graph to represent the topology of the environment, which allows for fast, coarse path planning. The coarse path is then refined via a heuristic pose fitting routine to ensure that the path is both collision-free and reduce unnecessary joint angle changes. The planner has been evaluated in simulation, demonstrating the feasibility of generating collision-free paths through narrow pathways for a reconfigurable robot.

This paper presents the motion planning framework for a hexapod, based on advanced motions, for accessing challenging spaces, namely narrow pathways and large holes, both of which are surrounded by walls. The advanced motions, wall and chimney walking, utilise environment surfaces that are perpendicular to the ground plane to support the robot motion. Such techniques have not yet been studied in the literature. The hierarchical planning framework proposed here is an extension to existing approaches which have only considered ground walking where foothold contacts are confined to the ground plane. During the pre-processing phase of the 2.5D grid map, the motion primitives employed are assessed for each cell and stacked to the graph if valid. The A* algorithm is then used to find a path to the goal position. Following that, the path is post-processed to smoothen the motions and generate a continuous path. Footholds are then selected along the path. The framework has been evaluated in simulation on the custom-designed Corin hexapod. The resulting path enables access to areas that are previously thought to be inaccessible and reduces the travelling distance compared to previous studies.