SoftVTBench: A Safety-Aware Visuo-Tactile Benchmark for Physically Constrained Robotic Manipulation of Deformable Objects
arXiv:2607.04234v1 Announce Type: cross Abstract: Deformable object manipulation poses challenges beyond task completion: successful execution must also maintain safe physical interaction, holding the object stably without slip or drop while avoiding excessive deformation. However, existing manipulation benchmarks are predominantly success-oriented and rarely evaluate whether a policy remains physically safe throughout execution. We present SoftVTBench, a safety-aware visuo-tactile benchmark for physically constrained deformable object manipulation. Built in Isaac Sim with finite-element-simul
The increasing sophistication of robotic manipulation tasks, particularly with deformable objects, necessitates a focus on safety and physical interaction beyond mere task completion, leading to the development of dedicated benchmarks.
This benchmark addresses a critical gap in robotic manipulation by integrating safety and physical constraints into the evaluation of deformable object handling, which is crucial for real-world deployment of advanced robots in sensitive environments.
The introduction of SoftVTBench shifts the focus of robotic manipulation development from purely success-oriented metrics to a more holistic evaluation that includes safety and physical interaction, fostering more robust and deployable robotic solutions.
- · Robotics research institutions (AI/RO)
- · Manufacturers of advanced robotic systems
- · Logistics and manufacturing sectors
- · Simulation software providers
- · Developers of unsafe/brittle robotic manipulation policies
- · Industries relying on purely task-oriented robotic solutions
- · Traditional robotic grippers without advanced sensing
Robotics development will increasingly prioritize safety and nuanced physical interaction, especially for deformable objects.
This will accelerate the adoption of visuo-tactile sensing and more sophisticated control algorithms in real-world robotic applications.
Improved safety and reliability in handling complex objects could significantly expand the addressable market for autonomous robots in sectors like healthcare, food processing, and customized manufacturing.
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Read at arXiv cs.AI