Inspired by the unique neurophysiology of the octopus, a hierarchical framework is proposed that simplifies the coordination of multiple soft arms by decomposing control into high‐level decision‐making, low‐level motor activation, and local reflexive behaviors via sensory feedback. When evaluated in the illustrative problem of a model octopus foraging for food, this hierarchical decomposition results in significant improvements relative to end‐to‐end methods. Performance is achieved through a mixed‐modes approach, whereby qualitatively different tasks are addressed via complementary control schemes. Herein, model‐free reinforcement learning is employed for high‐level decision‐making, while model‐based energy shaping takes care of arm‐level motor execution. To render the pairing computationally tenable, a novel neural network energy shaping (NN‐ES) controller is developed, achieving accurate motions with time‐to‐solutions 200 times faster than previous attempts. The hierarchical framework is then successfully deployed in increasingly challenging foraging scenarios, including an arena littered with obstacles in 3D space, demonstrating the viability of the approach.
The octopus coordinates multiple, highly flexible arms with the support of a complex distributed nervous system. The octopus’s suckers, staggered along each arm, are employed in a wide range of behaviors. Many of these behaviors, such as foraging in visually occluded spaces, are executed under conditions of limited or absent visual feedback. In coordinating unseen limbs with seemingly infinite degrees of freedom across a variety of adaptive behaviors, the octopus appears to have solved a significant control problem facing the field of soft-bodied robotics. To study the strategies that the octopus uses to find and capture prey within unseen spaces, we designed and 3D printed visually occluded foraging tasks and tracked arm motion as the octopus attempted to find and retrieve a food reward. By varying the location of the food reward within these tasks, we can characterize how the arms and suckers adapt to their environment to find and capture prey. We compared these results to simulated experimental conditions performed by a model octopus arm to isolate the primary mechanisms driving our experimental observations. We found that the octopus relies on a contact-based search strategy that emerges from local sucker coordination to simplify the control of its soft, highly flexible limbs.
more » « less- NSF-PAR ID:
- 10471737
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Bioinspiration & Biomimetics
- Volume:
- 18
- Issue:
- 6
- ISSN:
- 1748-3182
- Format(s):
- Medium: X Size: Article No. 066017
- Size(s):
- ["Article No. 066017"]
- Sponsoring Org:
- National Science Foundation
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Citizen‐science programs generally focus on the collection and analysis of observational data (e.g., bird checklists), but there has been increasing interest in the engagement of citizen scientists for ecological experimentation.
Our goal was to implement a behavioral experiment in which citizen scientists recorded antipredator behaviors in wild birds occupying urban areas. In North America, increasing populations of
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Using a randomized control–treatment design, citizen scientists at 15 sites recorded behaviors from 3891 individual birds representing 22 species. Birds were more vigilant and foraged less during the playback of a hawk call, and these responses were strongest for individuals within larger flocks and weakest in larger‐bodied birds. We did not find effects of sentinel species, tree cover, or urbanization.
By deploying a behavioral experiment, we found that backyard birds inhabiting urban landscapes largely maintained antipredator behaviors of increased vigilance and decreased foraging in response to predator cues. Experimentation in citizen science poses challenges (e.g., observation bias, sample size limitations, and reduced complexity in protocol design), but unlike programs focused solely on observational data, experimentation allows researchers to disentangle the complex factors underlying animal behavior and species interactions.
