Papers
2
Total Citations
13
H-Index
2
About
Dylan Swart is a roboticist whose work focuses on the control and optimization of legged and hybrid locomotion systems, pushing the boundaries of how robots navigate complex, real-world terrain. His research centers on bipedal balancing and trajectory optimization for ground robots that combine legs, wheels, and tracks. Swart’s major contribution is the development of a force-based double support balancing controller for bipedal robots operating on dynamic, uneven, and non-rigid terrain—a critical step toward making humanoid robots viable outside the lab. This work, validated on the "Tallahassee Cassie" platform, has garnered 10 citations and addresses a fundamental challenge in field robotics. He has also advanced trajectory optimization for hybrid track-leg and wheel-leg robots, formulating smooth analytical derivatives to enable these versatile machines to surmount large obstacles with greater efficiency. Though early in his career, Swart’s work is notable for its direct experimental validation on physical hardware, bridging the gap between simulation and deployment. His contributions are shaping the future of agile, all-terrain robots for applications in search-and-rescue, exploration, and beyond.
Research Focus
Key Achievements
Top Papers
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- 2