KinDER is a new open-source benchmark that demonstrates substantial gaps in current robot learning and planning methods for handling physical constraints.
Differentiable physics and stable modes for tool-use and manipulation planning,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
DynaRetarget refines human kinematic motions into dynamically feasible humanoid trajectories using incremental sampling-based trajectory optimization, achieving higher success rates than prior methods on diverse object interaction tasks.
citing papers explorer
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KinDER: A Physical Reasoning Benchmark for Robot Learning and Planning
KinDER is a new open-source benchmark that demonstrates substantial gaps in current robot learning and planning methods for handling physical constraints.
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DynaRetarget: Dynamically-Feasible Retargeting using Sampling-Based Trajectory Optimization
DynaRetarget refines human kinematic motions into dynamically feasible humanoid trajectories using incremental sampling-based trajectory optimization, achieving higher success rates than prior methods on diverse object interaction tasks.