arXiv:2606.10267v1 Announce Type: cross Abstract: Hierarchical vision-language-action (Hi-VLA) systems have emerged as a promising paradigm for complex robot manipulation, by using high-level VLM planners to decompose tasks into language subgoals executed by low-level VLA controllers. Despite recent empirical progress, there is a lack of unified design principles for these systems: existing Hi-VLA systems differ in how they choose and connect planners, controllers, mechanisms to switch between the two, and how observations and memory are represented in the planner. In this paper, we present a
The proliferation of complex VLM and VLA systems for robotics necessitates a systematic approach to hierarchical orchestration to move beyond empirical progress.
Establishing unified design principles for hierarchical robot agents is critical for scaling complex manipulation tasks, impacting both research and commercial applications of robotics and AI.
The focus is shifting from disparate implementations to standardized and efficient orchestration of multi-level AI models within robotic systems.
- · Robotics companies
- · AI research institutions
- · Automation sector
Improved performance and reliability of robotic manipulation for complex tasks.
Accelerated development and deployment of autonomous robotic systems in various industries.
Enhanced integration of AI agents with physical systems, expanding the scope of AI applications.
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