Marine robots are an increasingly attractive means for observing and monitoring in the ocean, but underwater acoustic communication (“acomms”) remains a major challenge, especially for real-time control. Packet loss occurs widely, bit rates are low, and there are significant delays. We consider here strategies for feedback control with acomms links in either the sensor-controller channel, or the controller-actuator channel. On the controller-actuator side we implement sparse packetized predictive control (S-PPC), which simultaneously addresses packet-loss and the data rate limit. For the sensor-controller channel we study a modified information filter (MIF) in a Linear Quadratic Gaussian (LQG) control scheme. Field experiments were carried out with both approaches, regulating crosstrack error in a robotic kayak using acomms. Outcomes with both the S-PPC and MIF LQG confirm that good performance is achievable.

We make two contributions toward integrated monitoring over large spatial scales, with multiple collaborating vehicles. Our focus is dynamic ocean features such as fronts and plumes. To support strong networked-control designs, we first develop a clean linear time-invariant framework for tracking features, that directly couples the global structure of the process to vehicle positioning. To address the packet loss inherent in underwater acoustic communications, we then extend the synthesis technique of Imer et al. [1] to the case where measurements and control commands suffer loss with differing statistics among the multiple channels. Simulations show that the integrated feedback system achieves good performance in front tracking.

We have developed an underwater vehicle that offers significant performance improvements over existing sub sea elevators. Our Vertical Glider Robot falls under its own weight to a precise location on the seafloor, employing streamlining, active steering, and basic navigation instrumentation. We examine typical at-sea mission requirements, mention several key governing parameters, and outline our design approach. We then describe a prototype device, and present results from model-scale experiments.