Body undulation used by snakes and the physical architecture of a snake body may offer significant benefits over typical legged or wheeled locomotion designs in certain types of scenarios. A large number of research groups have developed snake-inspired robots to exploit these benefits. The purpose of this paper is to report different types of snake-inspired robot designs and categorize them based on their main characteristics. For each category, we discuss their relative advantages and disadvantages. This paper will assist in familiarizing a newcomer to the field with the existing designs and their distinguishing features. We hope that by studying existing robots, future designers will be able to create new designs by adopting features from successful robots. The paper also summarizes the design challenges associated with the further advancement of the field and deploying snake-inspired robots in practice.

The use of bio-inspiration for the development of new products and devices requires new educational tools for students consisting of appropriate design and manufacturing technologies, as well as curriculum. At the University of Maryland, new educational tools have been developed that introduce bio-inspired product realization to undergraduate Mechanical Engineering students. These tools include the development of a bio-inspired design repository, a concurrent fabrication and assembly manufacturing technology, a series of undergraduate curriculum modules, and a new senior elective in the bio-inspired robotics area. This paper first presents an overview of the two new design and manufacturing technologies that enable students to realize bio-inspired products, and describes how these technologies are integrated into the undergraduate educational experience. Then, the undergraduate curriculum modules are presented, which provide students with the fundamental design and manufacturing principles needed to support bio-inspired product and device development. Finally, an elective bio-inspired robotics project course is present, which provides undergraduates with the opportunity to demonstrate the application of the knowledge acquired through the curriculum modules in their senior year using the new design and manufacturing technologies.

Cutter engagement is a measure that describes what portion of the cutter is involved in machining at a given instant of time. During profile milling of complex geometries, cutter engagement varies significantly along the cutter path. Cutter engagement information helps in determining the efficiency of the cutter path and also helps in improving it by adjusting the feed rate. This paper describes geometric algorithms for computing piece-wise continuous closedform cutter engagement functions for 2.5D milling operations. The results produced by our algorithm are compared with the results obtained by discrete simulations of the cutting process and appear to match very well.

Physical parameters of the constituent modules and gait parameters affect the overall performance of snake-inspired robots. Hence, a system-level optimization model needs to concurrently optimize the module parameters and the gait. Incorporating a physics-based model of rectilinear gaits in the system-level optimization model is a computationally challenging problem. This paper presents a case study to illustrate how metamodels of the precomputed optimal rectilinear gaits can be utilized to reduce the complexity of the system-level optimization model. An example is presented to illustrate the importance of concurrently optimizing the module parameters and the gait to obtain the optimal performance for a given mission.

Physical parameters of modules and gait parameters affect the overall snake-inspired robot performance. Hence the system-level optimization model has to concurrently optimize the module parameters and the gait. The equations of motion associated with the rectilinear gait are quite complex due to the changing topology of the rectilinear gait. Embedding these equations in the system-level optimization model leads to a computationally challenging formulation. This paper presents a system-level optimization model that utilizes a hierarchical optimization approach and meta-models of the pre-computed optimal gaits to reduce the complexity of the optimization model. This approach enabled us to use an experimentally validated physics-based model of the rectilinear gait and yet at the same time enabled us to create a system-level optimization model with a manageable complexity. A detailed case study is presented to show the importance of concurrently optimizing the module parameters and the gait using our model to obtain the optimal performance for a given mission.