Bioinspired Transformable Robot for Construction in Harsh Environments

Symmetry in Legged Robots

Motivation

In response to challenges posed by extreme environments, traditional construction methods lack efficiency and safety. The bioinspired transformable robot offers a solution by drawing inspiration from nature’s resilience. With its adaptability and agility, this robot revolutionizes construction practices in harsh conditions, reducing reliance on manual labor and minimizing risks to human workers. Moreover, its sustainable operation aligns with environmental stewardship goals, addressing immediate construction needs while promoting long-term sustainability.

Objective

The objective of this project is to create a highly adaptable legged robot with multifunctional capabilities, capable of autonomously morphing into diverse bioinspired forms. This robot aims to seamlessly adapt to a range of construction tasks across different project phases, ensuring maximum efficiency and versatility. From initial site preparation to intricate structural framing, roofing, and beyond, the robot will dynamically adjust to the specific demands of each task, enhancing the overall construction process.

Proposed Approach

Symmetry in legged robots manifests in various forms: a legged system may exhibit consistent gaits from any spatial starting point, maintaining identical leg movements on either side of the torso in phase; some systems also perform forward and backward movements that are so alike they seem to reverse time. In general, a symmetry of a legged robot can be defined as an invertible energy-preserving transformation that connects equivalent states across different regions of the phase space (Wieber, 2006). By applying group theory, each symmetry \( s \) is identified as an element of a group \( \mathbb{S} \), which is closed under the operations of composition \( \circ: \mathbb{S} \times \mathbb{S} \rightarrow \mathbb{S} \) and inversion \( (\cdot)^{-1}: \mathbb{S} \rightarrow \mathbb{S} \). From a practical perspective, the value of studying symmetries is underscored by their ability to relate the dynamics of a state \( (g, \xi, r, \dot{r}) \) with those of the symmetry-transformed state \( s(g, \xi, r, \dot{r}) \). This relationship suggests that effective modeling and control near any given state also enable control across all symmetrically equivalent states.