To better understand how animals make ethologically relevant decisions, we studied egg-laying substrate choice in
Drosophila
. We found that flies dynamically increase or decrease their egg-laying rates while exploring substrates so as to target eggs to the best, recently visited option. Visiting the best option typically yielded inhibition of egg laying on other substrates for many minutes. Our data support a model in which flies compare the current substrate’s value with an internally constructed expectation on the value of available options to regulate the likelihood of laying an egg. We show that dopamine neuron activity is critical for learning and/or expressing this expectation, similar to its role in certain tasks in vertebrates. Integrating sensory experiences over minutes to generate an estimate of the quality of available options allows flies to use a dynamic reference point for judging the current substrate and might be a general way in which decisions are made.
An adaptive switching controller based on dynamic zero moment point for versatile hip exoskeleton is proposed in this work. The linear finite hysteretic state machine is designed to recognize hybrid motion phases. The torque planning strategy based on dynamic zero moment point is deployed to obtain assistant torque adaptively under different locomotion. Experiments are carried out to verify the performance of the controller, confirming the stability and accuracy of the motion phase recognition, which also demonstrates excellent kinematic performance. The net metabolic rate can be reduced by 5.75% while wearing the versatile hip exoskeleton. Compared with existing research, the performance of the proposed controller has significant advantages. The proposed controller is capable of multiple types of locomotion including flat walking, stair climbing, and lifting heavy objects with low complexity and energy consumption.
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