IMBench: A Benchmark for Intuitive Robotic Manipulation
Researchers have introduced IMBench, a new benchmark designed to evaluate intuitive manipulation in robots by integrating perception, physical reasoning, action generation, and iterative execution. IMBench features 35 tasks and 14,000 filtered trajectories, requiring models to infer physical structure and generate feasible action sequences under explicit constraints. Initial experiments show that current vision-language and vision-language-action models struggle to combine reasoning with executable plans and to generalize across diverse manipulation scenarios.
Why it matters: IMBench highlights a significant gap in current AI and robotics systems' ability to integrate reasoning with action execution, which is crucial for developing more adaptive and capable robotic manipulation.
Full story at: arXiv Robotics ↗