India charts national robotics roadmap, calls for policy push and indigenisation

Key Takeaways

  • India has charted a national robotics roadmap to build global competitiveness in Physical AI and robotics through indigenisation.
  • The roadmap calls for a coherent national policy and incentive framework to strengthen domestic manufacturing and reduce import dependence in robotics.
  • Key themes of the roadmap include the need for sector-specific priorities such as collaborative robots and physical AI for healthcare.

New Delhi: The Technology Advisory Group (TAG) set up under the Empowered Technology Group (ETG) held its third meeting in the national capital.

On February 3, Principal Scientific Adviser Prof. Ajay Kumar Sood chaired a meeting to assess India’s current robotics capabilities and identify the structural gaps that need to be addressed to build global competitiveness in Physical AI and robotics.

During the meeting deliberations were held on the urgent need for a coherent national policy and incentive framework to strengthen domestic manufacturing and reduce import dependence in robotics.

In his keynote address, Prof. Sood highlighted the vision for a self-reliant India in Robotics through indigenisation.

He spoke about the paradigm shift in robotics, and strategic focus on augmentation rather than replacing human labour. Need for sector-specific priorities such as collaborative robots and physical AI for healthcare, unmanned and dual-use platforms for defence and internal security were highlighted.

In a statement, the Office of Principal Scientific Advisor to GoI, stated that the participants stressed that public procurement policies must be calibrated to balance cost, quality and technological depth, so that Indian firms are not crowded out by imports while still being pushed to meet global benchmarks. This approach was seen as essential to nurturing a robust homegrown robotics industry.

Stakeholders flagged significant vulnerabilities in the hardware and component ecosystem, noting gaps in actuators, sensors, transducers, chipsets, precision gears and advanced design and simulation tools. These deficiencies were described as strategic risks, particularly for defence and critical infrastructure sectors. As a result, a phased indigenisation strategy for critical components, backed by targeted R&D and manufacturing support, emerged as a major recommendation.

Another key theme was the need to strengthen India’s testing, certification and standardisation infrastructure. Participants highlighted that the absence of unified regulatory and safety frameworks not only poses domestic deployment risks but also acts as a non-tariff barrier to exports. Setting up accredited testing laboratories and aligning Indian standards with global norms such as ISO and CE certification was identified as vital for enabling Indian robotics products to compete in international markets.

The meeting also underscored the importance of building shared national data resources and federated digital infrastructure to support robotics innovation. Such an ecosystem would enable access to high-quality, task-specific datasets across sectors like defence, healthcare and agriculture, while also supporting supply-chain resilience and the indigenisation of software tools. This digital backbone was seen as critical for democratising innovation, accelerating deployment and strengthening talent development.

Participants emphasised that technology development must be driven by real-world needs rather than supply-led innovation. There was consensus on prioritising end-user engagement, defining user-driven key performance indicators (KPIs), and focusing on high-impact domains. Haptics and tactile intelligence were identified as foundational technologies for embodied AI, warranting dedicated national attention.

To accelerate progress, the group called for mission-oriented funding and innovation mechanisms, including grand challenges on the lines of the iDEX model and the use of schemes such as RDI to create dedicated funding channels for robotics. A Product Development and Partnership (PDP) model was proposed to overcome fragmentation between academia, industry and government, alongside MSME clustering, shared infrastructure and structured field and clinical validation to translate research into deployable products.

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