Senseandavoid

Sense-and-avoid (SAA) refers to the capability of a vehicle or robot to detect potential collisions and take action to maintain safe separation without real-time human input. It is central to unmanned aerial systems (UAS) and is increasingly used in autonomous ground, maritime, and aerial platforms, as well as consumer vehicles that support advanced driver-assistance features.

Sensing modalities commonly employed include cameras, LiDAR, radar, sonar, and ultrasonic sensors. These inputs are fused and processed by perception and fusion algorithms to detect obstacles, estimate their relative position and velocity, and predict their trajectories. Based on this information, a risk assessment evaluates potential conflicts and identifies feasible avoidance maneuvers. Path planning and low-level control then generate commands to adjust speed, change heading, alter altitude, or stop, while maintaining adherence to safety constraints and mission objectives. The system may also request human intervention if uncertainty remains high.

Regulatory and standards developments increasingly require sense-and-avoid or detect-and-avoid capabilities for certain operations, especially beyond-visual-line-of-sight aviation, with emphasis on reliability, latency, and fail-safe behavior. Field deployments span drone delivery, infrastructure inspection, robotics, and autonomous vehicles, often as part of broader collision avoidance or autonomy stacks.

Challenges include sensor limitations under adverse weather, latency, sensor fusion complexity, computational requirements, and the need for extensive validation to ensure robust performance in dynamic environments. Privacy, security, and ethical considerations are also addressed in deployment.