Background

In 2025, Americans are expected to spend a total of $1.47 Trillion dollars through online retail, a staggering 9.78% increase from the year prior [1]. In 2024, 18.4% of retail sales were completed online, requiring retailers to ship products from fulfillment centers directly to consumers with an ever-increasing desire for speed and accuracy. As result, online retailers are turning their sights to automated methods, leveraging Automated Mobile Robots (AMR) and areal drones. While great success has been achieved in the deployment of these technologies, they have primarily been managed as isolated deployments; controlling only one type of robot at a time. Systems such as Amazon Robotics ground-only approach introduces congestion on the warehouse floor and leaves volumetric space unused. The Collaborative Autonomous Robotics Platform (CARP) aims to orchestrate varying robotic modalities within a shared, physical operating environment. Because each robot variant can have drastically different capabilities, the system operates at both the micro and macro level. Upon receiving a request for a product, CARP identifies the optimum strategy to complete the task using the best combination of robots and existing infrastructure for the job. This combination of system types enables highly efficient space utilization. For example, a ground-based robot can collect heavy objects stored near ground level, meanwhile, a drone is flying above collecting lightweight merchandise. Built-in optimization algorithms consolidate merchandise for longer distance travel, freeing robots to accomplish nearby tasks and reducing energy and maintenance costs.

This system innovates upon three key aspects: