Jonathan Robert Salton

Using parallel stiffness to achieve improved locomotive efficiency with the Sandia STEPPR robot

In this paper we introduce STEPPR (Sandia Transmission-Efficient Prototype Promoting Research), a bipedal robot designed to explore efficient bipedal walking. The initial iteration of this robot achieves efficient motions through powerful electromagnetic actuators and highly back-drivable synthetic rope transmissions. We show how the addition of parallel elastic elements at select joints is predicted to provide substantial energetic benefits: reducing cost of transport by 30 to 50 percent. Two joints in particular, hip roll and ankle pitch, reduce dissipated power over three very different gait types: human walking, human-like robot walking, and crouched robot walking. Joint springs based on this analysis are tested and validated experimentally. Finally, this paper concludes with the design of two unique parallel spring mechanisms to be added to the current STEPPR robot in order to provide improved locomotive efficiency.

Parallel Elastic Elements Improve Energy Efficiency on the STEPPR Bipedal Walking Robot

This paper describes how parallel elastic elements can be used to reduce energy consumption in the electric-motor-driven, fully actuated, Sandia Transmission-Efficient Prototype Promoting Research (STEPPR) bipedal walking robot without compromising or significantly limiting locomotive behaviors. A physically motivated approach is used to illustrate how selectively engaging springs for hip adduction and ankle flexion predict benefits for three different flat-ground walking gaits: human walking, human-like robot walking, and crouched robot walking. Based on locomotion data, springs are designed and substantial reductions in power consumption are demonstrated using a bench dynamometer. These lessons are then applied to STEPPR, a fully actuated bipedal robot designed to explore the impact of tailored joint mechanisms on walking efficiency. Featuring high-torque brushless DC motors, efficient low-ratio transmissions, and high-fidelity torque control, STEPPR provides the ability to incorporate novel joint-level mechanisms without dramatically altering high-level control. Unique parallel elastic designs are incorporated into STEPPR, and walking data show that hip adduction and ankle flexion springs significantly reduce the required actuator energy at those joints for several gaits. These results suggest that parallel joint springs offer a promising means of supporting quasi-static joint torques due to body mass during walking, relieving motors of the need to support these torques and substantially improving locomotive energy efficiency.

Chile identification for metrics in the chile industry

This paper presents a novel approach to identify chile pods in two dimensional images of chile harvests in order to quantitatively evaluate harvesting and cleaning systems. Chilies vary greatly in shape, color, and texture throughout the season and within varieties and thus pose a unique challenge compared to the identification of other more uniform objects. Since chilies do not have distinct point features typically exploited in object recognition algorithms, a normalized shape distribution function was used to describe each objects general shape. 486 harvest object images were collected throughout the season and then placed in categories. Representative shape functions were derived from chilies in a given category and the other chilies, stems, and leaves were compared to each class. Sample shape distributions were found to provide a robust signature to discriminate among chile pods and harvest trash objects.