具身认知
计算机科学
工程类
人机交互
控制工程
人工智能
作者
Chang Liu,Mark Plecnik
标识
DOI:10.1177/02783649251360814
摘要
Repetitive subtasks of locomotion are offloaded from a conventional computer-actuator-sensor set-up to automatic mechanical processes. The subtasks considered are: (1) when out-of-contact with the environment, move a leg to a ready position in preparation for step contact, and (2) when contact is detected, push off the ground. Using conventional closed-loop control, subtask (1) would be accomplished by programming logic and a feedback loop onto a computer-motor-encoder system, and subtask (2) would be accomplished by sensing contact, then commanding the leg motor to push-off via programmed computer logic. We demonstrate how to transition this programmed logic from a computer processor to a mechanical processor. The mechanical processor performs preprogrammed actions based on combinations of states of components, some of which are internal and some that interact with the environment. Because signals are not digital, but rather mechanical quantities of energy, position, and force; transitioning to a mechanical processor enables a third subtask not possible by the computer alone: that is, (3) the accumulation of elastic energy while out-of-contact with the environment, and its automatic release upon contact for a more powerful push-off motion. Migrating processing out of the computer reduces the number of transduction steps, allows for faster responses to dynamic events, and instantiates a high-powered reflex triggered by ground contact. To illustrate these benefits, a robot with built-in onboard mechanical processing is compared to a conventional robot with logic executed by an offboard computer.
科研通智能强力驱动
Strongly Powered by AbleSci AI