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. 2022 Jul 11:9:860020.
doi: 10.3389/frobt.2022.860020. eCollection 2022.

Design Optimization for Rough Terrain Traversal Using a Compliant, Continuum-Joint, Quadruped Robot

Vallan Sherrod  1 , Curtis C Johnson  1 , Marc D Killpack  1
Affiliations

Design Optimization for Rough Terrain Traversal Using a Compliant, Continuum-Joint, Quadruped Robot

Vallan Sherrod et al. Front Robot AI. .

Abstract

Legged robots have the potential to cover terrain not accessible to wheel-based robots and vehicles. This makes them better suited to perform tasks such as search and rescue in real-world unstructured environments. In addition, pneumatically-actuated, compliant robots may be more suited than their rigid counterparts to real-world unstructured environments with humans where unintentional contact or impact may occur. In this work, we define design metrics for legged robots that evaluate their ability to traverse unstructured terrain, carry payloads, find stable footholds, and move in desired directions. These metrics are demonstrated and validated in a multi-objective design optimization of 10 variables for a 16 degree of freedom, pneumatically actuated, continuum joint quadruped. We also present and validate approximations to preserve numerical tractability for any similar high degree of freedom optimization problem. Finally, we show that the design trends uncovered by our optimization hold in two hardware experiments using robot legs with continuum joints that are built based on the optimization results.

Keywords: configuration space approximation; continuum robot; design metrics; evolutionary optimization; genetic algorithm; multi-objective optimization; quadruped design; soft robot.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
(A) A visualization of the walking region W. (B) The free body diagram of a single leg cut away from the body and making contact with the ground. The green circles represent joints as lumped particles, the black lines represent rigid links whose actual geometry is being optimized, and the dotted line represents the ground plane.
FIGURE 2
FIGURE 2
Diagram showing the horizontal foothold projection (left) and an simplified isometric view of the robot (right). Static analysis shows the force required of the leg at foothold 1 has a lower bound of N = 0 occurs when the CoM is over point A, as shown in the isometric view. The upper bound N = F robot /2 occurs when the CoM is over point B.
FIGURE 3
FIGURE 3
A flow chart visualizing the general approximation method as outlined in detail in Algorithm 1. The red cubes indicate an example of a foothold combination.
FIGURE 4
FIGURE 4
Top and side view of the simple four-DoF quadruped design.
FIGURE 5
FIGURE 5
Visualization of the support polygon and the static stability margin and longitudinal stability margin.
FIGURE 6
FIGURE 6
Illustration of the calculation of the approximation of average static stability criteria metric. The highlighted red squares indicate an example sampling of the possible footholds of the quadruped from its four legs.
FIGURE 7
FIGURE 7
(A): An illustration of the leg of the robot. Joint 1 is a two-DOF, eight-bellows, pneumatically-actuated, continuum joint. Joint 2 is a two-DoF, four-bellows, pneumatically-actuated, continuum joint. The valve block actuates Joint 2. A foot is attached to the end of Link 2. (B): A top view of the model of the body of the quadruped. Valves needed to actuate Joint 1 are included in this model.
FIGURE 8
FIGURE 8
(A) The Pareto front of the optimization after 60 generations represented in a scatter plot matrix. The robots with the best dexterity in walking region, average payload, average stability criteria, and averaged desired velocity are labeled as A, B, C, and D respectively. (B) The Pareto front of the optimization after 60 generations. The robots with the best dexterity in walking region, average payload, average stability criteria, and averaged desired velocity are labeled as A, B, C, and D respectively.
FIGURE 9
FIGURE 9
Visualization of designs (A–D). Axis units are in meters. Rigid links are shown in black while the pneumatic joints are shown in green. The red outline on the heat map is a projection of the quadruped body (solid red) onto the x − y plane for visualization clarity.
FIGURE 10
FIGURE 10
The frame orientations of a constructed leg used in the experiments with the HTC Vive trackers attached to sense its configuration.
See this image and copyright information in PMC

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