Design optimization of a 4-bar exoskeleton with natural trajectories using unique gait-based synthesis approach

Abstract Strolling is a complex activity that requires the synchronization of the brain, anxiety, and muscles, as well as rhythmic movement of the lower limbs. Gait may be abnormal if coordination is disrupted. As a result, exoskeletons should be used to treat it effectively. The connection and other systems contained in the exoskeletons could be used to mimic the behavior of the human lower leg. These mechanisms are created utilizing complex traditional methods. This study proposes a new gait-inspired method based on a genetic algorithm (GA) for synthesizing a four-bar mechanism for exoskeletons. For each phase of the gait, the trajectory is calculated and merged using optimization algorithms. Each phase of the trajectory passes through 10 precision points, for an entirety of 20 precision points in 1 gait cycle. For the problem under consideration, it is discovered that the GA outperforms other literature techniques. Finally, the proposed design for a lower limb exoskeleton is depicted as a solid model. Furthermore, the generated link-age accurately tracks all the transition points, and the simulation of the planned linkage for one gait cycle has been illustrated using a stick diagram.