This paper presents a constraint-aware decentralized approach to construction with teams of robots. We present an extension to existing work on a distributed controller for robotic construction of simple structures. Our previous work described a set of adaptive algorithms for constructing truss structures given a target geometry using continuous and graph-based equal-mass partitioning [1], [2]. Using this work as a foundation, we present an algorithm which performs construction tasks and conforms to physical constraints while considering those constraints to parallelize tasks. This is accomplished by defining a mass function which reflects the priority of part placement and prevents physically impossible states. This mass function generates a set of pointmasses in ℝn, and we present a novel algorithm for finding a locally optimal, equal-mass, convex tessellation of such a set.

Our prior work presented a decentralized algorithm for coordinating the construction of truss shaped objects out of multiple components (rods and connectors). In this paper, we consider how to transfer the theory to practice, implementing the algorithm to create a decentralized multi robot construction system. The system is composed of mobile manipulators and smarts parts with an embedded communication device. We discuss the delivery and assembly algorithms that comprise this system and the assumptions behind them. We present data from extensive hardware experiments with 4 robots coordinating an assembly task.

We develop a methodology for absolute encoding of spherical motion. This is accomplished by painting the surface of a moving sphere in two colors and sensing the color at a finite set of points. We show how point measurements on the sphere can resolve an arbitrary rotation to within a range depending on the number of sensors and the painting of the sphere. These techniques are applied to a prototype. The implementation of this prototype is discussed.