An SOS-certified adaptive Bug2 planner using second-order IK approximation and the S-procedure achieves zero joint-limit violations and 100% goal success across 94 adversarial test scenarios.
Real-time obstacle avoidance for manipulators and mobile robots
4 Pith papers cite this work. Polarity classification is still indexing.
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A new alignment heuristic and star-shaped simplex chain construction for feedback motion planning reduces average path bending by 91.4% and LQR effort by 45.5% while remaining computationally efficient.
A QP-designed C^∞-smooth vector field paired with an analytic nonlinear controller enables safe, input-constrained unicycle navigation to goals with faster convergence and lower turning effort than baselines.
CoFL learns continuous flow fields from BEV images and language instructions to generate navigation trajectories, outperforming modular VLM planners and trajectory policies on unseen scenes.
citing papers explorer
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Verified Task-Space Motion Planning Under Joint-Space Constraints
An SOS-certified adaptive Bug2 planner using second-order IK approximation and the S-procedure achieves zero joint-limit violations and 100% goal success across 94 adversarial test scenarios.
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Smooth Feedback Motion Planning with Reduced Curvature
A new alignment heuristic and star-shaped simplex chain construction for feedback motion planning reduces average path bending by 91.4% and LQR effort by 45.5% while remaining computationally efficient.
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Planning Smooth and Safe Control Laws for a Unicycle Robot Among Obstacles
A QP-designed C^∞-smooth vector field paired with an analytic nonlinear controller enables safe, input-constrained unicycle navigation to goals with faster convergence and lower turning effort than baselines.
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CoFL: Continuous Flow Fields for Language-Conditioned Navigation
CoFL learns continuous flow fields from BEV images and language instructions to generate navigation trajectories, outperforming modular VLM planners and trajectory policies on unseen scenes.