We present hardware, perception, and planning tools that enable a modular robot to autonomously deploy passive structures to reach otherwise-inaccessible regions of the environment to accomplish high-level tasks. An environment characterization algorithm identifies features in the environment that can be augmented to create a path between two disconnected regions of the environment. Specially-designed building blocks enable the robot to create structures that can augment the identified features to expand the reachable space of the robot. A high-level planner reasons about the high-level task, robot locomotion capabilities, and the environment to decide if and where to augment the environment in order to perform the desired task. These autonomous, perception-driven augmentation tools extend the adaptive capabilities of modular robot systems.
 The main difficulty of construction automation is the variety of materials. To cope with this problem, we propose a concept of automated assembly system for a modular structure. This system uses passive building blocks called "structure modules" and an assembler robot that is specialized to handle them. This "modular" concept drastically simplifies structural construction and allows automation. This paper describes the hardware design of the structure module and the assembler robots. Especially, the connection mechanism, the essential element of the system, is explained in detail. We built a prototype model based on the design to evaluate its automatic construction capability. Some experimental results illustrate the feasibility of the proposed method. We present the methodology, algorithms, system design, and experiments addressing the self-assembly of large teams of autonomous robotic boats into floating platforms. Identical self-propelled robotic boats autonomously dock together and form connected structures with controllable variable stiffness. These structures can self-reconfigure into arbitrary shapes limited only by the number of rectangular elements assembled in brick-like patterns. An @math complexity algorithm automatically generates assembly plans which maximize opportunities for parallelism while constructing operator-specified target configurations with @math components. The system further features an @math complexity algorithm for the concurrent assignment and planning of trajectories from @math free robots to the growing structure. Such peer-to-peer assembly among modular robots compares favorably to a single active element assembling passive components in terms of both construction rate and potential robustness through redundancy. We describe hardware and software techniques to facilitate reliable docking of elements in the presence of estimation and actuation errors, and we consider how these local variable stiffness connections may be used to control the structural properties of the larger assembly. Assembly experiments validate these ideas in a fleet of 0.5 m long modular robotic boats with onboard thrusters, active connectors, and embedded computers.