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Avidbots Neo 2WvsDoosan Robotics H2017

Side-by-side comparison of Avidbots Neo 2W and Doosan Robotics H2017: specs, price, use cases and SDKs.

Specifications

SpecNeo 2WH2017
Price (USD)
$60,000
$38,000
Category
industrial
industrial
Payload
0 kg
25 kg
Runtime
14 h
Speed
1.1 m/s
Weight
320 kg
79 kg
Reach
1700mm
Degrees of Freedom
6
Battery
Li-ion 48V
Shared use cases
No shared use cases
Only on Neo 2W
  • Warehouse floor cleaning
  • Retail store hours-after cleaning
  • Airport terminal cleaning
  • Manufacturing facility maintenance
Only on H2017
  • Heavy palletizing
  • Automotive component handling
  • Press-tending
  • Machine loading

When to pick which

When to pick Neo 2W

Choose the Avidbots Neo 2W when your primary operational bottleneck is facility hygiene in high-traffic, large-scale environments like international airport terminals or 24/7 distribution centers. While the $60,000 price point is higher, its 14-hour runtime and autonomous navigation allow for continuous floor maintenance across thousands of square meters without human intervention. It is the superior choice for facility managers who need to automate sanitation at scale. The integration with Avidbots Command Center and fleet analytics makes it ideal for multi-site deployments where centralized reporting on cleaning productivity is a requirement for operational transparency.

When to pick H2017

Select the Doosan Robotics H2017 for precision material handling and heavy-duty manufacturing tasks such as automotive component assembly or end-of-line palletizing. At $38,000, it offers a cost-effective solution for lifting 25kg payloads with a significant 1700mm reach. This cobot is designed for production floor integration where space is constrained but high repeatability is needed for press-tending or machine loading. Its support for ROS2 and DRL scripting makes it the better option for engineering teams requiring deep customization of robotic arm movements to optimize cycle times in a fixed workstation environment where floor cleaning is not the objective.

AI-generated buyer guidance based on public specs.

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