A Modular AgenticAI Architecture for Commercially Scalable and Compliant Robotics
Sahil Rajesh Dhayalkar, Brain Corporation
Autonomous navigation in dynamic environments faces immense challenges. Traditional rigid, rules-based systems often fail due to a lack of semantic understanding needed to adapt to continuous environmental shifts. Conversely, emerging end-to-end Vision-Language-Action (VLA) models introduce a critical "black box" dilemma; they inherently lack the explicit application context, deterministic guardrails, and data efficiency required for rigorous enterprise safety and compliance (e.g., SOC2). To address this, Brain Corp, in collaboration with UCSD, proposes a robust hybrid architecture underpinning the BrainOS platform. In this framework, visual inputs (via VLMs) and task commands (via LLMs) feed directly into a distinct Perception block anchored by a Contextual Grounding Layer with Semantic Mapping. This rich, grounded perception then informs a hybrid Action block, where the reasoning capabilities of VLA models operate safely alongside proven deterministic controls such as deep learning, reinforcement learning, model predictive control, etc. Crucially, an underlying Directed Safety Layer and strict Enterprise Infrastructure wrap this entire process. By isolating adaptable AI reasoning from hard-coded physical controls, this architecture provides a framework designed to securely manage the unpredictable realities of varied environments. Ultimately, this approach addresses the compliance bottleneck, laying the foundation to scale safely across diverse commercial applications and power the continuous, real-world data engine necessary to fuel next-generation physical AI.
Sahil Rajesh Dhayalkar is a Staff Autonomy Engineer and Perception Team Lead at Brain Corporation. He specializes in architecting real-time perception pipelines across LiDAR, RGB, and depth sensors, with his work currently deployed on production robots in dynamic commercial environments. During his tenure, he has pioneered the real-time computer vision pipeline for on-robot object detection at the edge, spearheaded "Localize From Anywhere," a global localization system utilizing Vision-Language Models and RGB images, and auto-calibration, a targetless calibration of ranging sensors on robots. He holds a Master's degree in Computer Science from Arizona State University. His research interests include robotic perception, large language models, deep learning, neuro-symbolic reasoning, and optimizations.
TILOS Seminar: Engineering the Future of Software with AI
Dr. Ruchir Puri, Chief Scientist, IBM Research, IBM Fellow, Vice-President IBM Corporate Technology
Software has become woven into every aspect of our society, and it will be fair to say that “Software has eaten the world”. More recently, advances in AI are starting to transform every aspect of our society as well. These two tectonic forces of transformation – “Software” and “AI” are colliding together resulting in a seismic shift – a future where software itself will be built, maintained, and operated by AI – pushing us towards a future where “Computers can program themselves!” In this talk, we will discuss these forces of “AI for Code” and how the future of software engineering is being redefined by AI.
Dr. Ruchir Puri is the Chief Scientist of IBM Research, an IBM Fellow, and Vice-President of IBM Corporate Technology. He led IBM Watson as its CTO and Chief Architect from 2016-19 and has held various technical, research, and engineering leadership roles across IBM’s AI and Research businesses. Dr. Puri is a Fellow of the IEEE, and has been an ACM Distinguished Speaker, an IEEE Distinguished Lecturer, and was awarded 2014 Asian American Engineer of the Year. Ruchir has been an adjunct professor at Columbia University, NY, and a visiting scientist at Stanford University, CA. He was honored with John Von-Neumann Chair at Institute of Discrete Mathematics at Bonn University, Germany. Dr. Puri is an inventor of over 70 United States patents and has authored over 100 scientific publications on software-hardware automation methods, microprocessor design, and optimization and AI algorithms. He is the chair of AAAI-IAAI conference that focused on industrial applications of AI. Ruchir is the recipient of the prestigious Distinguished Alumnus Award from Indian Institute of Technology (IIT), Kanpur in 2022.