RI: Medium: Dynamical Coordination and Sequencing of Multifunctionality in Animals and Robots

Case Western Reserve University, Cleveland OH

Investigators

Abstract

How can intelligent control be created for autonomous robots that will allow them to respond flexibly and adaptively to changing environments? In the animal world, relatively simple animals such as soft-bodied invertebrates, are capable of coordinating their many possible movements, flexibly shifting and sequencing multiple behaviors as conditions change, and learning to alter their behavior based on experience. For robots, however, this remains a challenge, which is addressed in this project using a novel control architecture that can produce sensory driven or cyclic movements. Traditional control architectures for robotics have three layers: high level deliberative planning, low-level reactive control, and an intermediate level for sequencing and simple decision-making. Creating intermediate level controllers for intelligent behavior is particularly challenging, and a major obstacle to progress in autonomous robotics. This problem will be addressed using a novel neural-inspired control architecture, stable heteroclinic channels (SHCs) that can flexibly and robustly orchestrate multiple degrees of freedom for multifunctionality, and can readily handle behavioral hierarchies, temporal decision-making, and learning. Their properties also allow them to incorporate some of the best aspects of the two traditional approaches to robotic control: finite state machines and central pattern generator (limit cycle) controllers. SHC-based dynamical architectures underlying multifunctionality will be analyzed in a soft-bodied animal that is tractable to experimentation, and principles from these neurobiological architectures will be used to implement multifunctional behavior in a novel hyper-redundant, soft-bodied robot platform. There are many possible applications for adaptive, flexibly-controlled soft-bodied, or hyper-redundant, robots that are able to coordinate their many degrees of freedom in varying ways to accomplish multiple functions. A multifunctional worm-like robot could crawl through pipes of varying diameter and at any angle with respect to gravity and make sharp turns at intersections. A hollow hyper-redundant robot could inspect water mains from the inside, without interrupting water flow. Such a robot could be used for oil and gas pipeline inspections to avoid costly and environmentally disastrous leaks. Smaller versions could be developed for endoscopic diagnosis of the gastrointestinal tract. The proposed work will lead to a single controller framework that can robustly coordinate multiple coupled actuated mechanisms within a robot, and describe the sequencing of distinct behaviors in both animals and robots.