Control of walking in the stick insect: From behavior and physiology to modeling

Classical engineering approaches to controlling a hexapod walker typically involve a central control instance that implements an abstract optimal gait pattern and relies on additional optimization criteria to generate referen ce signals for servocontrollers at all the joints. In contrast, the gait of the slow-walking stick insect apparently emerges from an extremely decentr alized architecture with separate step pattern generators for each leg, a s trong dependence on sensory feedback, and multiple, in part redundant, prim arily local interactions among the step pattern generators. Thus, stepping and step coordination do not reflect an explicit specification based on a g lobal optimization using a representation of the system and its environment ; instead they emerge from a distributed system and from the complex intera ction with the environment. A similarly decentralized control at the level of single leg joints also may explain the control of leg dynamics. Simulati ons show that negative feedback for control of body height and walking dire ction combined with positive feedback for generation of propulsion produce a simple, extremely decentralized system that can handle a wide variety of changes in the walking system and its environment. Thus, there is no need f or a central controller implementing global optimization. Furthermore, phys iological results indicate that the nervous system uses approximate algorit hms to achieve the desired behavioral output rather than an explicit, exact solution of the problem. Simulations and implementation of these design pr inciples are being used to test their utility for controlling six-legged wa lking machines.