Jory Denny
Papers
13
Total Citations
238
H-Index
9
About
Jory Denny is a leading researcher in robotics motion planning, whose work centers on developing efficient sampling-based algorithms that navigate complex, high-dimensional environments. His major contributions include pioneering region-biased and medial axis-guided techniques, such as Dynamic Region-biased RRTs and MARRT, which enable robots to find not just feasible paths, but safer, higher-clearance trajectories. Denny’s innovative Toggle PRM framework, with 33 citations, introduced a coordinated mapping of both free and obstacle spaces, fundamentally improving planning in arbitrary dimensions. His work on robust belief space planning (31 citations) extends these ideas to robots operating under motion and sensing uncertainty, with real-world validation on physical mobile robots. Denny has also advanced topology-guided roadmap construction for multi-robot coordination and protein-ligand binding problems, and explored user-guided planning theory and neural network-based collision prediction. With over 230 total citations across his most-cited works, Denny’s research bridges theoretical rigor and practical deployment, making him a key figure in enabling robots to plan safer, more reliable motions in dynamic, uncertain environments.
Research Focus
Key Achievements
Top Papers
- 1Dynamic Region-biased Rapidly-exploring Random Trees43 citations · 2020
- 2MARRT: Medial Axis biased rapidly-exploring random trees41 citations · 2014
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- 5Topology-Guided Roadmap Construction With Dynamic Region Sampling28 citations · 2020
- 6UMAPRM: Uniformly sampling the medial axis19 citations · 2014
- 7The Toggle Local Planner for sampling-based motion planning12 citations · 2012
- 8Toward realistic pursuit-evasion using a roadmap-based approach9 citations · 2011
- 9On the theory of user-guided planning9 citations · 2016
- 10Predicting Sample Collision with Neural Networks5 citations · 2020