TL;DR
Experimental results in various task scenarios show that the proposed framework consistently improves overall task success rates compared with unimodal settings with different LLMs and achieves a higher success rate compared to using only visual or force data.
VLA-SP (Vision-Language-Action via Symbolic Planning), a two-stage Embodied Vision-Language-Action framework, enabling fully automated robotic execution from speech and vision inputs is proposed, demonstrating the strong interpretability, executability, and cross-platform applicability of the framework.
A closed-loop framework for planning and evaluation of a vision-language model-based robotic manipulation agent operating in tabletop object rearrangement and manipulation tasks and demonstrates the potential of closed-loop vision-language planning for human-centered robotic manipulation.
Evidence Acquisition and Feasibility Gating (EAFG) is proposed, a framework that acquires visual evidence through VLM-generated exploratory subgoals and TAMP-based execution and applies a feasibility gate to decide whether to proceed with task planning, acquire further evidence, or halt.
Visual Embodied Brain-1.5 (VeBrain-1.5) is presented, a task-level unified framework that connects multimodal perception and spatial reasoning with robot control through a shared MLLM-compatible decision interface and shows strong adaptability, flexibility, and compositional capabilities compared to existing methods.
This study comparatively examines the task-oriented grasping problem, which is of critical importance in robotic manipulation, through modern Vision-Language Models. Within the scope of the study, the performance rates of the GraspMolmo model, specifically trained for robotic tasks, and Gemini ER-1.5, a general-purpose...
This work proposes APIVOT, a VLM-based planner that adaptively interleaves language and visual thoughts for long-horizon planning that outperforms general-purpose VLMs and prior planning frameworks, achieving the largest gains in spatially constrained settings.
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