Denso integrates LiDAR sensing with autonomous forklifts for automated logistics at inverter manufacturing facility.
Denso and Toyota Industries have started automated truck loading and unloading operations at Denso’s Anjo plant in Japan. The deployment was announced on 26 October 2026. The system combines Toyota Industries’ Rinova Autonomous forklift and Denso’s LiDsEYE LiDAR-based sensing system.
The objective is to automate cargo handling while improving safety through wider monitoring of people and obstacles across the truck yard.
Denso’s LiDsEYE uses LiDAR(light detection and ranging), a laser-based sending technology, to monitor the wider truck yard. Unlike the forklift’s onboard safety sensors, LiDsEYE extends monitoring beyond the vehicle’s immediate surroundings. The system detects people and obstacles in the truck-handling area. When a person enters the monitored area, the combined safety-support arrangement can stop the forklift.
Their system uses Toyota Industries’ Rinova Autonomous forklift. Its functions include detecting where a truck has stopped, identifying pallet positions and orientations, automatically generating travel routes, carrying out truck loading and unloading operations and using onboard obstacle detection for safety. The forklift currently relies on information collected through onboard cameras for its route-generation process.
The system is operational at Factory 204. The factory manufactures inverters. The deployment applies automated logistics technology within automotive parts and cargo configurations while coordinating material movements with production requirements.
Denso’s sensing components business unit supplies LiDsEYE. Its power electronics components business unit manages the overall operation at the plant; Toyota Industries supplies the Rinova Autonomous forklift and provides the autonomous cargo-handling technology.
The companies are testing LiDsEYE’s ability to recognize cargo positions and cargo dimensions and sizes. They are working to improve the system’s cargo recognition accuracy/ The next development stage involves incorporating LiDsEYE data into the forklift’s route-generation process.
The companies identified labour shortages and the need to improve working conditions as reasons for developing the system. Cargo handling in manufacturing facilities remains heavily dependent on manual labour.
