SECOM Japan Awarded “GOOD DESIGN AWARD 2022” With SECOM’s Security Robot, COCOBO

SECOM Japan has awarded “GOOD DESIGN AWARD 2022” with SECOM’s security robot, COCOBO.

COCOBO is an advanced autonomous security robot. It moves under autonomous control in crowded places, on bad roads outdoors, and elevators, and uses AI to recognize suspicious persons/objects, sensor arms to inspect trash cans and shadows, and displays to make announcements in the vicinity. COCOBO also has a function to block peripheral vision by emitting white smoke at the operator’s discretion.

The name “Cocobo” is derived from the idea of COgnitive COoperation RObots, designed to assist humans in different endeavors. Here are some another potential functions of Cocobo:

1. To Patrol on Behalf of Security Guards

   Cocobo travels autonomously along a pre-set patrol route, avoiding people and obstacles. In addition to being integrated with elevators and capable of patrolling areas with multiple floors, the waterproof feature allows it to patrol outdoors regardless of weather conditions. When the patrol is completed, it automatically returns to the charging dock.

2. To Cooperate with Security Guards in The Event of an Emergency

   AI analyzes the images captured by the camera in real time. If a suspicious object, a suspicious person, a fallen person, a person left behind, or fire is detected, Cocobo will notify the disaster prevention center and respond in cooperation with security guards. It can also conduct voice and light warnings, as well as smoke intimidating functions, in case a suspicious person is detected.

3. To Perform Inspection Work Using an Arm and Multiple Attachments

   The attachment of the arm can be replaced according to usage. Inspections could be performed at the pre-set spots along the patrol route. Attachments with infrared sensors and visible cameras can be used to detect hazardous materials in trash cans and vending machines. Hand attachments can be used to open and close doors and check locks of doors (under development).

View full information on: https://www.g-mark.org/award/describe/53928?locale=en