AI-powered perception, planning and control for autonomous-mobility research. A modular autonomy platform that combines sensor perception, localisation, path planning, decision-making and safety monitoring for simulation, controlled pilots and mobility R&D.
Autonomous systems must interpret dynamic roads, objects, lanes and changing environmental conditions. Data from multiple sensors must be synchronised into a reliable world model at ultra-low latency.
Ingests and synchronises camera, radar, LiDAR and positioning signals. Detects lanes, vehicles, and drivable space using perception models. Combines behaviour planning and path generation.
Sensor Fusion, Perception AI, Path Planning, Safety Monitoring
Autonomy R&D (Mobility & Automotive)
Planning and control decisions must be made at low latency with predictable safety behaviour.
The AI engine continuously builds a 3D semantic map of its surroundings, emitting virtual LiDAR and Radar pulses. By tracking objects and projecting their vectors, the autopilot can confidently plan safe, smooth trajectories even in dense traffic scenarios.
A clear operational flow combines automation, configurable controls and accountable human oversight.
Capture synchronised data from vehicle and environment sensors. This includes multi-camera arrays, LiDAR point clouds, and high-precision GPS.
Build a tracked scene model with lanes, objects and free space. Sensor fusion algorithms merge diverse inputs into a unified representation of the world.
Select optimal behaviour and generate a safe, feasible trajectory. Path planning handles obstacle avoidance and traffic rule adherence.
Send control commands (steering, throttle, braking) while monitoring hardware limits and engaging fallback safety protocols instantly if discrepancies arise.
A modular autonomy stack connects multi-sensor perception with planning, control, telemetry and safety oversight.
| Data/Sensors | Camera, radar, LiDAR, GPS and IMU integration |
| AI/Pipeline | Detection, tracking, multi-modal fusion and map localisation |
| Logic/Planning | Behaviour selection, trajectory generation, and PID control |
| Review/Control | Telemetry, remote monitoring constraints, replay and validation |
The implementation of this AI solution yielded significant results and benefits for the client, transforming their R&D capabilities.
Provides reusable autonomy modules for focused pilots and experiments.
Captures sensor, decision and intervention data for rigorous scenario replay.
Allows sensors, models and control interfaces to be easily swapped and adapted.
Separates operational logic from safety monitoring and controlled fallback behavior.
