Passive Simultaneous Localization and Mapping (SLAM) for Terminal Guidance
AI Overview
This SBIR seeks passive SLAM technology enabling small unmanned aircraft to autonomously navigate complex environments using onboard sensors and compute. The solution must identify obstacles, plan dynamic routes to static or moving targets, and maintain accuracy without external connectivity or cloud support.
This summary is AI-generated from the official solicitation.
Key Details
Official Description
This topic seeks innovative research and development efforts that allow Special Operations Soldiers to employ autonomously navigating Group 1 UAS in complex, cluttered, and unstructured environments. OWA UAS often have some level of autonomous terminal guidance when a target is verified and approved for targeting. Basic UAS terminal guidance capabilities typically utilize computer vision to develop bounding boxes on a selected target and navigate directly to that location. Utilizing a designated...
Change History
Passive Simultaneous Localization and Mapping (SLAM) for Terminal Guidance
Status changed from Pre-Release to Open
Passive Simultaneous Localization and Mapping (SLAM) for Terminal Guidance
# Q&A Changes Summary **New Question Added:** - Q1: Clarifies that terminal guidance range is a key Phase I deliverable, to be determined by speed + camera + compute analysis rather than pre-specified. **No Material Changes:** Questions Q2-Q5 remain identical to previous version with consistent answers on passive-only sensing, real-time processing requirements, non-cooperative tracking in denied environments, and day/night operations in DDIL settings. **Note:** Q4 and Q5 in the updated version appear truncated (Q5 cuts off at "14. Evaluation metrics..."), so full comparison of Phase I feasibility evidence and Phase II demonstration expectations cannot be completed.
Passive Simultaneous Localization and Mapping (SLAM) for Terminal Guidance
**Summary of Q&A Changes:** **New Questions Added (Q3):** Seven substantive questions added covering sensing modalities, real-time processing requirements, target behavior assumptions, cooperative vs. non-cooperative tracking, environmental conditions, compute constraints, and Phase I evaluation metrics. **Key Clarifications:** - **Sensing:** Passive sensors only; near-infrared laser ranging explicitly prohibited (Q1, Q2) - **Target Behavior:** Targets assumed to maneuver erratically in non-cooperative, denied environments—not pre-defined trajectories - **Real-Time Processing:** Required onboard; no hard latency specs if performance criteria met - **Compute:** No specific platform mandates; solutions must not degrade Group 1 UAS performance - **Operations:** Day/night capable in rural/urban DDIL environments - **Phase I Metrics:** Success measured on target interdiction rates, obstacle avoidance reliability, and SWAP (not specific accuracy thresholds yet) **Notable:** Answers emphasize operational realism (adversarial targets, GPS denial, non-cooperative tracking) while maintaining flexibility on technical implementation details.
Passive Simultaneous Localization and Mapping (SLAM) for Terminal Guidance
This content specifies technical requirements for autonomous terminal guidance of Group 1 drones in GPS-denied environments using passive sensors, requiring ROS2/Docker architecture, visual odometry at 100Hz, operation on edge devices (Jetson/Voxl2), and obstacle avoidance in forested/rural, maritime, and rubble terrain.
Passive Simultaneous Localization and Mapping (SLAM) for Terminal Guidance
New opportunity: Passive Simultaneous Localization and Mapping (SLAM) for Terminal Guidance
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