Delivery Robot S2


Segway robotics S2 is a delivery robot developed to meet the intensive delivery needs of different built environment and usage scenario

Creating new distribution experiences

 

Multi-box delivery  |  Core battery, odometry and electronic control technologies  |  Multi-robots collaboration  | Sensory fusion mapping

 

S2 offers a safer and more intelligent, efficient and reliable delivery experience to consumers.

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Directional guide robot | Deliver items for customers | Audio broadcast | 24/7 scheduled services | Security Robot Patrol with Video Surveillance

IoT-based elevator | Intelligent obstacle avoidance | Autonomous navigation | Automated recharging

How does S2 complete the delivery process?

The delivery robot can adapts well to slow-moving objects in the environment. It integrates visual navigation and laser ranging sensors to more accurately sense the surrounding terrain.

S2 carries out mapping and plan its path on its own, and can achieve 360o Omni-directional obstacle avoidance to fulfil various delivery needs. 

Localization and navigation algorithm

Indoor type of built environments are generally more challenging for an autonomous ground vehicle due to the surrounding is design to support foot traffic and human activities. 

LiDAR + Visual SLAM

Developed after multiple iterations, a fusion of sensors constructed SLAM and with the navigation, the algorithm realizes three-dimensional autonomous localization and mapping. At the same time, 3D ground detection sensors and the recent visual segmentation algorithm are added to greatly enhance operational safety.

Efficient obstacle avoidance by intelligent sensing

Based on the latest research achievement on reinforced learning, S2 can easily detect low obstacles such as human feet and steps in crowded environments such as shopping mall, healthcare institution, transit hub and office buildings.

Autonomously adapt to environmental changes

Continuous map update and information correlation during its operation, it adapts to working environment changes. With mapping for one time, it can maintain fully autonomous localization for a longer period, and until the location experienced substantial structural changes.

Robot fleet management and scheduling

A robust system of mapping and navigation algorithm was further refined and enhanced by cloud service network to deliver intelligent dynamic scheduling and real-time service monitoring, without any manual maintenance.

Enhanced by big data and machine learning

  • Cloud-based scheduling
  • Real-time service monitoring
  • Remote & Navigation cloud service
  • Path specific elevator call
  • Data & statistics