  Current rigid linkage grippers are limited in flexibility, and gripper design
optimality relies on expertise, experiments, or arbitrary parameters. Our
proposed rigid gripper can accommodate irregular and off-center objects through
a whippletree mechanism, improving adaptability. We present a whippletree-based
rigid under-actuated gripper and its parametric design multi-objective
optimization for a one-wall climbing task. Our proposed objective function
considers kinematics and grasping forces simultaneously with a mathematical
metric based on a model of an object environment. Our multi-objective problem
is formulated as a single kinematic objective function with auto-tuning
force-based weight. Our results indicate that our proposed objective function
determines optimal parameters and kinematic ranges for our under-actuated
gripper in the task environment with sufficient grasping forces.
