The age of autonomous mobile systems is dawning -- from autonomous cars to household robots to aerial drones -- and they are expected to transform multiple industries and have significant impact on the US economy. Through wireless coordination, these systems create a whole that is greater than the sum of its parts. For example, vehicle "platoons" increase both highway throughput and fuel efficiency by traveling nearly bumper-to-bumper, using a wireless coupling to brake and accelerate simultaneously. Similarly, vehicles or drones can speed around blind corners using the sensing capabilities of the agents ahead of them. However, wireless communication is still considered too unreliable for safety-critical operations like these. This research is creating new techniques for safe wirelessly coordinated mobility, which is becoming increasingly important with the proliferation of autonomous mobile systems. The approach is to develop a framework for joint modeling and analysis of motion and communication in order to find provably safe coordination paths. This includes new models that can predict the effect of motion paths on the wireless channel, together with new formal methods that can use these models in a tractable manner to synthesize control strategies with provable guarantees. The key innovations include new methods to assess the validity of a Radio Frequency model, new methods for tractable probabilistic reasoning over complex models of the wireless channel and protocols, and new control strategies that achieve provable safety guarantees for states that would have been unsafe without wireless coordination. If successful, this research will allow mobile systems to realize the performance benefits of wireless coordination while preserving the ability to provide provable safety guarantees. The focus is not on improving the wireless channel reliability; instead, the aim is to provide safety guarantees on the entire mobile system by modeling and analyzing the channel's dynamic properties in a rapidly changing environment.