The increase in e-commerce and corresponding supply-chain demand will pressure the traditional manufacturing and warehouse material handling models. Product variations like size, handling robustness, and stiffness, along with seasonal demand fluctuations, drive the need to have a flexible and scalable workspace. Current warehouse and manufacturing automation systems, including QR code, RF-tag location mapping, and safety cell-based robot systems are efficient, but constrain the effectiveness of the facility and lack the multisensory force feedback, flexibility, and scalability of humans.

In projects evaluating new technologies, supporting startups, government agencies, Tier 1’s, and global OEMs, the overarching question is how to achieve increased productivity. Recently, terms like the Internet of things (IoT) and Industry 4.0 have become commonplace, but what disruptive technologies will deliver on these promises?


Cobots (robots which collaborate with humans) are vital to improving operational efficiency. Enabling material handling robots to adapt to new roles, adjust to workspace envelopes automatically, and use manipulation approaches based on product characteristics would facilitate efficient, safe, flexible, and scalable operations.

With recent advancements in autonomous vehicle technologies, the potential exists to share a connected environment where robots and humans cohabit the same space. Advancements in cameras, ultrasonic, LiDAR, radar, and other detection technologies have overcome traditional limitations in environmental awareness, adaptability, and cost to deliver the required safety and enhanced productivity demanded.

New sensor technologies and associated object recognition algorithms facilitate robot-human workspace collaboration. The ability for robots to understand their environment and react to changes allows more efficient use of the available real estate and the possibility for their use in low volume multi-functional operations.

Table 1 ranks sensor technology by capability, where no one sensor type works across all tasks and conditions. Sensor fusion—the use of multiple sensors—provides a comprehensive environmental map, the necessary redundancy, and the improved robot capabilities crucial for cobot applications.

Other factors that could be considered but are not included in Table 1are color perception, sensor size, close-proximity object, optically concealed object, and sign recognition.

Performance/Business Metric

The cost of technological advancement comes with a price tag that drives the business decision. The recommended approach is to consider all pertinent metrics, e.g.

1. Warehouse floor space savings—reduced need for a safety zone

 2. Workforce optimization and fast reconfiguration that can evolve or change with the business environment

3. Efficiency improvements (process takt times)—balanced operations even at low throughput

4. Standardized maintenance—equipment and infrastructure

 5. Storage and logistics reconfigurability

 6. Safety—robots can have eyes in the back of their heads and reduced injury-related workers compensation

Future technologies harnessing sensor fusion with artificial intelligence will make robots capable of more tasks historically considered the domain of humans. Until robots can achieve the same dexterity and cognitive ability as humans, there will be a need for that human touch in every workplace. Cobots pave the way for the next step in productivity in a collaborative workspace shared by both humans and robots.