Trajectory Optimization for Cable-Driven Soft Robot Locomotion

Abstract

Compliance is a defining characteristic of biological systems. Understanding how to exploit soft materials as effectively as living creatures do is consequently a fundamental challenge that is key to recreating the complex array of motor skills displayed in nature. As an important step towards this grand challenge, we propose a model-based trajectory optimization method for dynamic, cable-driven soft robot locomotion. To derive this trajectory optimization formulation, we begin by modeling soft robots using the Finite Element Method. Through a numerically robust implicit time integration scheme, forward dynamics simulations are used to predict the motion of the robot over arbitrarily long time horizons. Leveraging sensitivity analysis, we show how to efficiently compute analytic derivatives that encode the way in which entire motion trajectories change with respect to parameters that control cable contractions. This information is then used in a forward shooting method to automatically generate optimal locomotion trajectories starting from high-level goals such as the target walking speed or direction. We demonstrate the efficacy of our method by generating and analyzing locomotion gaits for multiple soft robots. Our results include both simulation and fabricated prototypes.

Real2Sim

“…Auzinger et al [2018] also successfully employed a similar formulation to optimize 3D printed nanostructures for desired light transport properties such as refraction. Bern et al [2019] use a direct sensitivity analysis approach to optimize for cyclic locomotion trajectories of soft robots. We use their simulation framework combined with our parameter estimation system for the demo application shown in Fig.…”

“…We then use the same mesh and parameters, adding some elements representing the weight of the motors, and design a control strategy for this robot in simulation. The ground contact and tendon actuation forces are simulated using the method of [Bern et al 2019]. The use of an intentionally coarse mesh greatly speeds up motion planning.…”

Origami Pump Actuator Based Pneumatic Quadruped Robot (OPARO)

“…To generate specific motions, there are multiple options of actuating mechanisms. For instance, the developers can select pneumatic [3], [4], [7], [9], [23], [31], hydraulic [24], electromagnetic [35], combustive [36], tendon-driven [7], [37], [38], and motor-driven [39]. Also, we can fabricate soft robots by using a variety of materials: paper [4], [34], silicone [2], [3], [7], [31], [36], and foam [37], [38].…”

“…For instance, the developers can select pneumatic [3], [4], [7], [9], [23], [31], hydraulic [24], electromagnetic [35], combustive [36], tendon-driven [7], [37], [38], and motor-driven [39]. Also, we can fabricate soft robots by using a variety of materials: paper [4], [34], silicone [2], [3], [7], [31], [36], and foam [37], [38]. Additionally, smart materials such as dielectric elastomers [8], [32], [33], [40], shape memory alloys [17], [34], [41], magnetoactive elastomers [35], and piezoelectrics [42] have been utilized to implement the actuations as well as their structures.…”

A Gait Pattern Generator for Closed-Loop Position Control of a Soft Walking Robot

“…In order to implement CPGs in a meaningful way, the basic gait pattern must therefore be known from the outset, which again is robot-specific. An example for the automatic generation of optimal joint-trajectories is given in Bern et al ( 2019 ). By using a forward shooting method and an FEM-based direct kinematics simulation, high-level goals, such as forward speed or direction of movement of various soft walking robots can be met.…”