According to the researchers, existing voice-controlled home service robots typically cost between 150,000 and 250,000 rupees, placing them far beyond the reach of most households in developing economies. Those that are affordable tend to be narrow in capability, addressing a single subsystem such as autonomous movement or internet-of-things appliance control in isolation. And almost without exception, commercial platforms restrict voice interaction to English, excluding the hundreds of millions of users whose first languages are Hindi, Gujarati, or any of the other tongues spoken across linguistically diverse regions. Harley’s designers argue that no single commercial product currently combines mobile navigation, standard-protocol IoT control, and multilingual conversational AI at any comparable price point.

Technically, Harley rests on a deliberate division of labour between two compute tiers. A Raspberry Pi serves as the high-computing device, handling speech recognition, natural language understanding, navigation decision-making, and the coordination of subsystems. An ESP32 microcontroller sits at the other end of the architecture, tasked with driving the relays and circuits that switch high-power household appliances safely. The bridge between them is MQTT, the lightweight publish-subscribe messaging protocol that has become a de facto standard in industrial and consumer IoT deployments. By structuring communication around MQTT topics, the team decoupled the intelligence layer from the actuation layer, allowing the Raspberry Pi to issue commands to the ESP32 without direct electrical coupling and making the appliance-control subsystem extensible to any MQTT-compliant device.

The conversational layer is powered by the Google Gemini API, which the robot uses to interpret spoken commands and generate context-aware responses across multiple languages. Rather than relying on rigid, keyword-matched command grammars, Harley pipes captured speech to the large language model, which can handle paraphrase, mixed-language utterances, and open-ended questions in addition to discrete instructions such as switching off a fan or navigating to the kitchen. The researchers report that this integration enabled natural, context-aware communication, and that in experimental trials the system earned an average conversational quality rating of 4.1 out of 5.0 across multiple languages — a figure that, while drawn from their own residential evaluation, suggests the interaction model was judged substantially better than the brittle command-and-response behaviour typical of low-cost voice devices.

Navigation is the third pillar of the design. Harley supports voice-enabled navigation commands that direct the robot to predefined locations inside the home, using stored coordinates recorded within the environment. In practice, a user can ask the robot to travel to a named waypoint — a room, a charging dock, or a designated position — and the robot plans and executes the movement autonomously. The waypoint approach trades the complexity of full simultaneous localisation and mapping for a simpler, more robust scheme suited to static home layouts, and it keeps the computational burden low enough to run on modest hardware. The team notes that experimental validation in a residential setting measuring 75 square metres across four rooms demonstrated a high voice recognition accuracy and an improved navigation success rate alongside reliable appliance control with low latency.

The economics of the build are arguably its most striking feature. The researchers itemised the total component cost of Harley at 9,247 rupees, which they benchmarked against a mid-range alternative configuration assembled from commercial off-the-shelf parts at 47,850 rupees — an 80 percent component-level saving. Compared with the 150,000 to 250,000 rupee range quoted for existing voice-controlled home service robots, Harley comes in at roughly 19 percent of the cost of an equivalent system, and a small fraction of the premium end of the market. The authors frame this not merely as an engineering achievement but as a question of access: high-performance home automation robotics, they argue, is achievable at a fraction of current market cost, with particular relevance to multilingual and cost-sensitive environments, including those serving elderly users in developing economies.

That last point carries social weight. India’s ageing population, like much of Asia’s, is growing faster than the infrastructure available to support it, and voice-first interfaces are among the most accessible technologies for users with limited mobility, declining eyesight, or low digital literacy. A robot that understands commands in a user’s native language and can physically move through the home — fetching itself to a bedside, switching appliances, answering questions — addresses a genuinely different user group than the wall-mounted smart speakers and app-controlled plug ecosystems that dominate the consumer market. The researchers position Harley within a broader body of work on service robots in aged care, noting that prior deployments have shown promise but frequently stumble on cost, language support, and the integration gap between mobility and control functions.

The study is candid about its experimental scope. Validation was conducted in a single residential setting rather than across a fleet of homes, and the waypoint-based navigation scheme presumes a relatively stable floor plan, meaning a significant rearrangement of furniture would require re-recording stored coordinates. The conversational quality scores, while encouraging, originate from the development team’s own evaluation, and larger, independent user studies with elderly and non-technical participants would be needed to establish how the system performs under real-world acoustic conditions, accents, and background noise. The cloud dependence of the Gemini API also raises questions about latency, privacy, and behaviour during internet outages — a consideration the authors’ own cited literature on offline voice interaction for elderly-care robots highlights as an open challenge in the field.

Even so, the work signals a shift in what low-cost robotics can credibly deliver. By pairing commodity single-board computers with lightweight IoT protocols and cloud-scale language models, small academic teams can now assemble systems that until recently demanded enterprise budgets. If the cost trajectory holds, the practical consequences could reach well beyond gadget enthusiasts: assistive robots for elderly users who speak minority languages, affordable automation for small clinics and care homes, and educational platforms that let students experiment with integrated robotics without institutional funding. The Nirma University team, which received no specific grant from any funding agency and developed the system with laboratory facilities and laser-cutting equipment at the institute, has demonstrated that the barrier to a genuinely useful, multilingual, mobile home robot is no longer primarily technical or financial — it is a matter of integration, and Harley shows one concrete way to close it.

Subject of Research: A low-cost multilingual voice-interactive home service robot integrating navigation, IoT control, and conversational AI

Article Title: Harley: a voice interactive intelligent robot for home services and automation

Article References: Chokshi, T., Shah, D., & Pandya, V. (2026). Harley: a voice interactive intelligent robot for home services and automation. International Journal of Intelligent Robotics and Applications. https://doi.org/10.1007/s41315-026-00587-y

Image Credits: AI Generated

DOI: 10.1007/s41315-026-00587-y

Keywords: robotics, home automation, voice interaction, MQTT, Raspberry Pi, ESP32, conversational AI, Google Gemini, indoor navigation, IoT, multilingual technology, assistive robots