SeekSense provides a robot‑agnostic software layer that converts high‑level task requests into executable action plans for any mobile robot platform. It delivers continuous environment modeling, adaptive planning, and modular perception through ROS and REST/GraphQL APIs, allowing dynamic navigation and payload handling without re‑engineering.
Funding
Funding not disclosed
Founders
Product
Problem
Mobile robot deployments often fail when the operating environment changes, because each robot relies on tightly coupled, platform‑specific software that cannot generalize across layouts or tasks. This fragility forces frequent re‑engineering and limits the scalability of automation in dynamic settings such as warehouses, hospitals, or factories.
Solution
SeekSense provides a robot‑agnostic software layer that converts high‑level task requests (e.g., “go to aisle 3, locate the red box, deliver it to station 5”) into executable action plans for any mobile robot platform. The platform leverages a unified perception‑planning stack with continuous environment modeling, enabling dynamic path planning and on‑the‑fly adaptation as obstacles or layouts shift. By abstracting navigation, object localization, and payload handling into reusable modules, developers can deploy new routines without rewriting low‑level code. The system also incorporates incremental learning to refine map accuracy and task efficiency over time, reducing the need for manual re‑calibration. Integration points include ROS‑compatible APIs, RESTful services, and optional edge‑runtime containers for on‑robot execution.
Target Audience
Primary customers are robot manufacturers and enterprise automation teams in logistics, manufacturing, and facilities management that require a reliable, platform‑independent solution for mobile robot task execution.
Features
- Cross‑robot abstraction layer that maps declarative task intents to robot‑specific motion primitives
- Continuous environment modeling using incremental SLAM and semantic labeling for real‑time obstacle avoidance
- Adaptive task planner that re‑optimizes routes when layout changes are detected, minimizing downtime
- Modular perception stack with vision‑based object detection and pose estimation, configurable for diverse payloads
- ROS 2 and ROS 1 bridge, plus REST/GraphQL APIs for seamless integration with existing fleet‑management systems
- Edge‑runtime container that runs the planning engine locally, ensuring low latency and offline operation
- Built‑in telemetry and performance analytics dashboard for monitoring task success rates and learning progress