Edge AI Robotics
Compute, Perception and On-Device Navigation for Warehouse AMRs
- Robots in Pilot Zone
- 20
- On-Robot NPU (INT8)
- 4 TOPS
- Obstacle-Classification Accuracy
- 98.5%
- Bench-tested
Wearables, vehicles and robotics
Robotics engineering for industrial, collaborative and autonomous systems, covering control electronics, real-time firmware, ROS 2 integration, motor control, sensor fusion, embedded computer vision and functional safety.
Every project is quoted as a fixed-scope proposal within 3–5 business days of a discovery call. Discuss your product
Edge AI Robotics
Compute, Perception and On-Device Navigation for Warehouse AMRs
Capabilities
BLDC and PMSM drivers with field-oriented control (FOC), encoder and Hall feedback, current sensing and fault protection, for joints, grippers and drive wheels.
Real-time firmware on the motor and sensor controllers, bridged to ROS 2 on the robot computer, with Nav2 or MoveIt 2 where the robot needs them.
IMU, encoder, LiDAR and camera fusion with Kalman filtering, and embedded vision models running on the robot, measured on the target hardware.
Safety functions designed to ISO 13849 and ISO 10218-1/-2:2025 requirements (ISO 3691-4 for mobile robots): emergency stop, safe torque off and speed and separation monitoring.
Process
Analyse the requirements, check technical feasibility and component availability, and agree the milestones.
Deliverable: Technical requirements document, project milestones and risk assessment
Detailed system design and component selection, with design review, signal-integrity and power analysis.
Deliverable: System architecture, schematic, PCB layout and firmware architecture
Prototype hardware fabrication and firmware development, with code reviews and hardware verification.
Deliverable: Prototype hardware, firmware codebase, test procedures and documentation
Functional, environmental and regulatory testing against the requirements.
Deliverable: Test results report, compliance documentation and release package
Planning
Start with a non-confidential summary of your product and the milestone you need to reach next.
Flight controller vs companion computer, ESCs, LiPo, hybrid and hydrogen power, India’s Drone Rules and type certification, costs and timelines.
Consider sensing, calibration and integration choices for wearable and embedded motion applications.
Explore where FPGA acceleration fits an embedded inference pipeline and how it affects architecture choices.
Proof
Edge AI Robotics
E-commerce logistics provider
Robotic Prosthetic Arm
Prosthetics research institute
Dexterous Robotic Hand
Indian medical-device company
Robotic Arm Controller Board
Robotics evaluation-board project
EMG Sensor Front-End
Indian medical-device company
FAQ
We develop control electronics and software for autonomous mobile robots (AMRs), robotic arms and grippers, and UAV power and avionics studies. Our capabilities span motor control, sensor fusion, path planning and AI-based perception, working with your mechanical design team.
We primarily use ROS/ROS2 for complex robotic systems, with custom firmware for resource-constrained applications. Our software stack includes navigation (Nav2), computer vision (OpenCV, TensorFlow), motion planning (MoveIt), and simulation (Gazebo, Isaac Sim) tools.
Yes, we design safety functions to the requirements of ISO 10218-1/-2:2025 for industrial robots, ISO 13849 for safety-related control systems, and ISO 3691-4 for autonomous mobile robots. Our designs include safety PLCs, emergency stop systems and collision avoidance features; certification is carried out by an accredited body.
Sensor fusion combines data from multiple sensing modalities like LiDAR, cameras, IMUs, and ultrasonic sensors using algorithms like Extended Kalman Filters or particle filters to produce a unified environmental model more accurate than any single sensor alone. This compensates for individual sensor weaknesses, such as LiDAR's inability to detect transparent surfaces or camera degradation in low light.
Mobile robots commonly use A* or Dijkstra's algorithm for global path planning on known maps, combined with local planners like the Dynamic Window Approach (DWA) for real-time obstacle avoidance. For complex or high-dimensional spaces, sampling-based planners such as RRT* provide asymptotically optimal paths, while lattice-based planners generate kinematically feasible trajectories for non-holonomic robots.
ROS 2 is a middleware framework built on DDS (Data Distribution Service) that provides a publish-subscribe communication layer, hardware abstraction, and a rich ecosystem of packages for perception, navigation, and manipulation. Unlike ROS 1, ROS 2 supports real-time execution, multi-robot systems, and production-grade security with DDS-based access control.
Autonomous navigation in dynamic environments combines SLAM for building and updating spatial maps with predictive obstacle tracking using algorithms like velocity obstacles to anticipate moving agents. The navigation stack continuously replans paths using costmap layers that distinguish between static infrastructure and dynamic obstacles, enabling safe operation in warehouses, hospitals, or public spaces.
Collaborative robot safety systems implement ISO 10218-1/-2:2025 (which incorporates the former ISO/TS 15066 collaborative requirements) through speed and separation monitoring, power and force limiting, and safety-rated monitored stop functions using redundant sensor networks. We integrate 3D time-of-flight cameras and capacitive skin sensors to create dynamic safety zones that adjust robot speed based on human proximity.
Robotic arm motion planning uses forward and inverse kinematics solvers to map between joint space and Cartesian task space. Motion planning frameworks like MoveIt 2 layer collision-aware trajectory optimization on top, using OMPL planners to generate smooth, jerk-limited joint trajectories that avoid obstacles while respecting joint limits, velocity constraints, and payload dynamics.
Swarm robotics coordination uses decentralized algorithms inspired by biological systems, where individual robots follow simple local rules that produce emergent collective behaviors like formation control, area coverage, or cooperative transport. Communication is typically limited to local neighbor-to-neighbor messaging, ensuring the system scales gracefully and remains resilient to individual robot failures.
Robot simulation environments like Gazebo, NVIDIA Isaac Sim, or MuJoCo allow developers to test algorithms in physics-accurate virtual worlds before deploying to physical hardware, reducing development cycles and preventing costly damage. Digital twins extend this by maintaining a real-time synchronized virtual replica of a deployed robot, enabling remote monitoring, predictive maintenance, and what-if scenario testing.
Edge computing processes sensor data locally on the robot rather than round-tripping to the cloud, which is critical for real-time control loops requiring sub-10ms latency for tasks like obstacle avoidance or force feedback. We deploy optimized inference engines on edge GPUs like NVIDIA Jetson to run perception models locally, while offloading non-latency-sensitive tasks like map aggregation to cloud infrastructure.
Each project is quoted as a fixed-scope proposal: a statement of work with milestones, deliverables and pricing, sent within 3–5 business days of the discovery call. The price depends on the requirements, how mature the design is, technical complexity, the number of prototype iterations and the validation scope. Longer engagements can also run as a retainer or a hybrid of both. For budgeting before you contact us, our hardware development cost benchmarks and the PCB design, firmware and IoT cost guides give indicative ranges with their assumptions stated. They are planning ranges, not quotes.
It depends on the scope and on what already exists when we start. As planning ranges from our cost benchmarks: a single PCB layout takes 2–6 weeks per board and embedded firmware 4–16 weeks. A connected (IoT) product takes 3–12 months from concept to a production-ready design, and a regulated medical device 12–24 months to a 510(k) submission-ready package; from idea to mass production, a typical connected product takes 9–18 months. The proposal sets out a dated milestone plan, and you receive weekly progress updates during the project.
You do. Our contracts assign the intellectual property in the project work product (schematics, PCB design files, firmware source code and documentation) to you on payment, and we hand over the source files, not only fabrication outputs or compiled binaries. The exact terms are set out in the signed agreement for each engagement.
Yes. We sign a mutual NDA before any technical discussion of your project. Send your standard NDA or use ours; we return it signed within one business day.
Yes. We are based in Hyderabad, India, and work with product teams in India, the United States, the United Kingdom, Germany, Japan, Australia, the Middle East and other markets. Our office hours are 10:30–19:00 India Standard Time (UTC+5:30), Monday to Saturday, and we schedule design reviews across time zones, typically from US Pacific to Central European time. Japan is 3.5 hours ahead of India, so our first four hours overlap the Japanese afternoon. Prototypes and documentation ship by international courier such as DHL or FedEx. Our hardware outsourcing guide covers what to agree before an international project starts.
Yes. We prepare the manufacturing release package — fabrication and assembly drawings, the BOM with approved manufacturers, programming files and test specifications — and hand it over to the contract manufacturer (EMS) you choose. If you have not chosen one, we help you evaluate candidates through technical capability assessments and a pilot build. See manufacturing support.
No. Rapid Circuitry does not hold ISO 9001, ISO 13485 or other certificates. Our processes are aligned with ISO 9001:2015, and we design products to the requirements of the standards that apply to them — for example IEC 60601-1 and IEC 62304 for medical devices (with design documentation structured so your ISO 13485 quality system can absorb it) and IEC 61000 for EMC — and we specify IPC-A-610 workmanship classes for assembly. We prepare the product and its documentation for certification testing at accredited laboratories; the certificate or approval is issued for your product by the laboratory, notified body or regulator.
A short, non-confidential description of the product and what it must do (sensors, connectivity, on-device processing), the target production volume and unit cost, the markets and regulations it must meet (for example FDA, CE or FCC), your timeline, and what already exists: a concept, a proof of concept, schematics, PCB files or firmware. After the NDA, the next step is a 30-minute discovery call with the engineers who would work on the project, followed by the fixed-scope proposal. Send a project brief to begin.
Explore
System architecture, MCU/SoC selection, schematic and PCB design, board bring-up, validation and manufacturing handoff.
Embedded C/C++ firmware on bare metal, an RTOS or embedded Linux: drivers, bring-up, secure boot and OTA updates.
On-device inference: feasibility on your target hardware, model porting and quantisation, and integration with the firmware.