Collectives in nature demonstrate behaviors that extend far beyond the capabilities of any single agent. Social slime mold, for example, has thousands of cells that aggregate and form mobile and immobile nutrient-searching structures as a function of the chemical signaling between cells and their interactions with the surrounding environment. This species embodies many features that swarm roboticists wish to incorporate in self-reconfigurable robot collectives: emergent complexity, plasticity, and scalable constituents. This thesis argues that regardless of the length scale, we can implement some of the same principles and features to exploit robot morphology, physical interactions among agents, and low-level coordination mechanisms to enable diverse collective behaviors for useful applications across fields. In this thesis, I present novel emergent behaviors through physical robot collectives at the macro- and micron length scales and virtual collectives and explain how each behavior arises as a function of agents interacting with other agents, agents interacting with or reacting to their environment, and agents exploiting their environment to better influence other agents. I expand the relatively new field of mobile coupled oscillators. Specifically, I present a new iteration of the swarming coupled oscillator (swarmalator) model, which enables many new emergent collective behaviors in addition to those already shown in the literature. It also replicates many behaviors of natural and artificial collectives even though the detailed physical interactions are not taken into account. This abstract model has the potential to inform on the coordination mechanisms possible at different length scales. At the macro-scale communication-constrained coordination may serve as a fall-back, and at smaller length scales it may reveal some collective behaviors that are possible with agents that cannot currently have on-board processing. At the macro-scale, I present soft modular robot collectives that exhibit embodied intelligence by exploiting a tight coupling between sensing and actuation to enable reconfiguration, locomotion, and strain-based consensus among other collective behaviors. I have contributed to the development of various soft actuators, a sensor, and two different types of soft robot collectives with differing capabilities, and have studied these collectives using both physical hardware and simulations. At the micron scale, I present novel behaviors through magnetic microrobot collectives that use physical interactions between agents and their surrounding environment to enable the collective to perform on-demand reconfiguration of various functions and morphologies and manipulate passive objects in the surrounding environment. The microrobot collective behaviors are further studied through a physical model and a swarmalator model. The diverse collective behaviors presented in this thesis hold many potential applications in swarm robotics, self-reconfigurable modular robots, and small-scale manufacturing; additionally, they hold great value for fundamental scientific research in self-assembly, self-organization, and emergent complexity. This thesis expands the fields of soft robotics, microrobotics, and coupled oscillators and demonstrates the potential to unlock many new emergent collective behaviors by exploiting low-level sensing, actuation, and coordination mechanisms.