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Rendezvous with sperm whales for biological observations is made challenging by their prolonged dive patterns. Here, we propose an algorithmic framework that codevelops multiagent reinforcement learning–based routing (autonomy module) and synthetic aperture radar–based very high frequency (VHF) signal–based bearing estimation (sensing module) for maximizing rendezvous opportunities of autonomous robots with sperm whales. The sensing module is compatible with low-energy VHF tags commonly used for tracking wildlife. The autonomy module leverages in situ noisy bearing measurements of whale vocalizations, VHF tags, and whale dive behaviors to enable time-critical rendezvous of a robot team with multiple whales in simulation. We conducted experiments at sea in the native habitat of sperm whales using an “engineered whale”—a speedboat equipped with a VHF-emitting tag, emulating five distinct whale tracks, with different whale motions. The sensing module shows a median bearing error of 10.55° to the tag. Using bearing measurements to the engineered whale from an acoustic sensor and our sensing module, our autonomy module gives an aggregate rendezvous success rate of 81.31% for a 500-meter rendezvous distance using three robots in postprocessing. A second class of fielded experiments that used acoustic-only bearing measurements to three untagged sperm whales showed an aggregate rendezvous success rate of 68.68% for a 1000-meter rendezvous distance using two robots in postprocessing. We further validated these algorithms with several ablation studies using a sperm whale visual encounter dataset collected by marine biologists. 

Regulation systems for fluid-driven soft robots predominantly consist of inflexible and bulky components. These rigid structures considerably limit the adaptability and mobility of these robots. Soft valves in various forms for fluidic actuators have been developed, primarily fluidically or electrically driven. However, fluidic soft valves require external pressure sources that limit robot locomotion. State-of-the-art electrostatic valves are unable to modulate pressure beyond 3.5 kPa with a sufficient flow rate (>6 mL⋅min −1 ). In this work, we present an electrically powered soft valve for hydraulic actuators with mesoscale channels based on a different class of ultrahigh-power density dynamic dielectric elastomer actuators. The dynamic dielectric elastomer actuators (DEAs) are actuated at 500 Hz or above. These DEAs generate 300% higher blocked force compared with the dynamic DEAs in previous works and their loaded power density reaches 290 W⋅kg −1 at operating conditions. The soft valves are developed with compact (7 mm tall) and lightweight (0.35 g) dynamic DEAs, and they allow effective control of up to 51 kPa of pressure and a 40 mL⋅min −1 flow rate with a response time less than 0.1 s. The valves can also tune flow rates based on their driving voltages. Using the DEA soft valves, we demonstrate control of hydraulic actuators of different volumes and achieve independent control of multiple actuators powered by a single pressure source. This compact and lightweight DEA valve is capable of unprecedented electrical control of hydraulic actuators, showing the potential for future onboard motion control of soft fluid-driven robots. 

Today’s use of large-scale industrial robots is enabling extraordinary achievement on the assembly line, but these robots remain isolated from the humans on the factory floor because they are very powerful, and thus dangerous to be around. In contrast, the soft robotics research community has proposed soft robots that are safe for human environments. The current state of the art enables the creation of small-scale soft robotic devices. In this article we address the gap between small-scale soft robots and the need for human-sized safe robots by introducing a new soft robotic module and multiple human-scale robot configurations based on this module. We tackle large-scale soft robots by presenting a modular and reconfigurable soft robotic platform that can be used to build fully functional and untethered meter-scale soft robots. These findings indicate that a new wave of human-scale soft robots can be an alternative to classic rigid-bodied robots in tasks and environments where humans and machines can work side by side with capabilities that include, but are not limited to, autonomous legged locomotion and grasping.