Passive Morphological Adaptation for Obstacle Avoidance in a Self-Growing Robot Produced by Additive Manufacturing

Underground penetration and exploration technologies have a long history and can be exploited in many sectors, such as agriculture, for example, to define soil water content1; geology, for example, for terrain seismic profiling2 and underground characterization3; and the oil and gas industry4 or construction, for example, for mapping and maintenance of underground utility service infrastructures5 and tunneling.6 Autonomous solutions, which can monitor the surrounding environment, make decisions, and adjust their behavior for improving penetration and exploration, could help make the process faster, more reliable, cheaper, and safer for humans and underground infrastructures.7 However, robotic solutions for such applications are still very limited,8–13 due to the strong constraints imposed on the movement of autonomous systems below ground by the physics of such a cluttered environment (i.e., high pressure and friction, stratifications with different soil impedance, and rocks). Ideally, a robotic system moving in soil should be able to adapt its actions to unpredictable constraints, avoiding or navigating around obstacles or sensitive objects, for example, to prevent damaging underground pipes or objects of the cultural heritage. However, they have a limited possibility of perception compared to aboveground robots, which for instance can take advantage of vision. Thus, within the soil, a possible strategy for movement and exploration is for the morphology of the body to adapt itself to the soil structure. Morphological adaptation in artificial solutions has been particularly exploited in the field of soft-bodied robotic systems,14,15 where soft materials are adopted for the deformation of soft artificial bodies, for moving through small gates16,17 or navigating cluttered environments, for example, by exploiting the passive buckling ability of soft inflatable structures in a robot, without the use of a sensory perception or bending control.18 Material properties or soft actuators are used for enhancing robot abilities.19 In fact, the adaptation provided by soft materials and actuators can effectively improve robot behaviors while decreasing the control complexity.20,21