SUMMARY: Snake robots have the potential to make substantial contributions in areas such as rescue missions, firefighting, and maintenance where it may either be too narrow or too dangerous for personnel to operate. During the last 10–15 years, the published literature on snake robots has increased significantly. The purpose of this paper is to give a survey of the various mathematical models and motion patterns presented for snake robots. Both purely kinematic models and models including dynamics are investigated. Moreover, the different approaches to biologically inspired locomotion and artificially generated motion patterns for snake robots are discussed.

In nature, snakes can gracefully traverse a wide range of different and complex environments. Snake robots that can mimic this behaviour could be fitted with sensors and transport tools to hazardous or confined areas that other robots and humans are unable to access. In order to carry out such tasks, snake robots must have a high degree of awareness of their surroundings (i.e., perception-driven locomotion) and be capable of efficient obstacle exploitation (i.e., obstacle-aided locomotion) to gain propulsion. These aspects are pivotal in order to realise the large variety of possible snake robot applications in real-life operations such as fire-fighting, industrial inspection, search-and-rescue, and more. In this paper, we survey and discuss the state of the art, challenges, and possibilities of perception-driven obstacle-aided locomotion for snake robots. To this end, different levels of autonomy are identified for snake robots and categorised into environmental complexity, mission complexity, and external system independence. From this perspective, we present a step-wise approach on how to increment snake robot abilities within guidance, navigation, and control in order to target the different levels of autonomy. Pertinent to snake robots, we focus on current strategies for snake robot locomotion in the presence of obstacles. Moreover, we put obstacle-aided locomotion into the context of perception and mapping. Finally, we present an overview of relevant key technologies and methods within environment perception, mapping, and representation that constitute important aspects of perception-driven obstacle-aided locomotion.

Several design methods and principles have been presented so far, in order to guide the design of autonomous operations. Putting the required efforts into learning and using the methods for designing autonomous operations is a daunting task. Experiences so far have shown that the use of methods meant to the help the design process are often ignored. One reason could be that the design guidelines are too complex and contain much information often not relevant for the project at hand, and therefore there is no easy way to distinguish what is important from what is not. This is an issue that needs to be solved with our approach. In this article, the Autonomous Job Analysis (AJA) method is presented. The proposed methodology is created in order to guide the design of autonomous operations in maritime systems by breaking them down in to sub-operations in order to reveal challenges, needs and limitations regarding autonomous behavior. The canvas contains the categories of the AJA method on a single page format -the canvas- and each category is supported with questions to be asked during the design procedure, as well as example answers. We will describe the AJA method and the AJA canvas in detail, and present a use case scenario of an autonomous operation in order to show how they can be applied. The particular use-case is the design of an autonomous operation for the detection, inspection and tracking of a waste water plume.