Daniel M. Bodily

Papers

Total Citations

H-Index

About

Daniel M. Bodily is a robotics researcher whose work centers on the design optimization and motion planning of both soft and rigid robotic systems. His research bridges the gap between intelligent algorithm development and practical robotic implementation, with a particular focus on pneumatically actuated and inflatable manipulators. In his highly cited 2017 work on multi-objective design optimization of soft pneumatic robots, Bodily introduced a novel fitness-function-based framework that evaluates candidate designs according to platform-specific metrics such as dexterity and load-bearing capacity, earning 32 citations and establishing him as a contributor to the emerging field of soft robotics. Complementing this, his motion planning research introduced an innovative inverse kinematics branching algorithm that simultaneously optimizes a mobile robot's base position and joint trajectories to achieve smooth end-effector motion, accumulating 28 citations. Together, these contributions reflect a cohesive research vision: making robotic systems more adaptable, safer, and computationally intelligent. Bodily's 2017 output, spanning multiple publications, demonstrates a productive period of foundational work that continues to influence researchers working at the intersection of soft robotics, kinematics, and automated design.