Search for: All records

Recent work in the design of mechanical systems for terrestrial locomotion has indicated successful strategies for increasing the energetic performance of a robotic locomotor without upgrading its actuator system. We apply one such strategy, termed power modulation, in a new way: for the design of a leg mechanism useful for running. Power modulation geometrically defines force/torque ratios between robot components to mechanically achieve certain energy transmission characteristics during fast stance dynamics that increase the kinetic power output of the overall system. Furthermore, we investigate the design of a leg mechanism that can adjust to exhibit power modulation. In this way, a leg mechanism would exhibit a low power mode for flat terrain, and can adjust to a high power mode for rough terrain. The latter makes jumping possible and extends the range of available footholds that can be accessed in a single step. To find a suitable leg mechanism, we leverage the Finite Root Generation method to compute a design. The design is advanced to a prototype and basic experiments are conducted to investigate its behavior as adjusted between high-and low-power modes 

Due to high impact forces and low duty cycles, monopedal jumping robots are particularly susceptible to failure from a slipping foot. Spines provide a solution to reduce slip, but there has been little research on how to effectively engage them into a surface with a dynamic jumping robot. Previous robots utilizing spines operate in different regimes of surface approach speed and cycle time. For a penetrable substrate, spines must be directed into the surface at suitable holding angles, then extracted before the foot leaves the ground. We accomplished this by designing a gripper mechanism for the robot Salto that pushes in angled spines along their length and is kinematically constrained to engage/disengage with leg crouch/extension. The resulting mechanism introduces no new actuators, enables jumping on penetrable inclines up to 60 degrees and enables static adhesion to hold 7.5 times the robot’s weight from a ceiling. 

This study presents new results on a method to solve large kinematic synthesis systems termed Finite Root Generation. The method reduces the number of startpoints used in homotopy continuation to find all the roots of a kinematic synthesis system. For a single execution, many start systems are generated with corresponding startpoints using a random process such that startpoints only track to finite roots. Current methods are burdened by computations of roots to infinity. New results include a characterization of scaling for different problem sizes, a technique for scaling down problems using cognate symmetries, and an application for the design of a spined pinch gripper mechanism. We show that the expected number of iterations to perform increases approximately linearly with the quantity of finite roots for a given synthesis problem. An implementation that effectively scales the four-bar path synthesis problem by six using its cognate structure found 100% of roots in an average of 16,546 iterations over ten executions. This marks a roughly six-fold improvement over the basic implementation of the algorithm.