Robotics & Automation News

Market trends and business perspectives

Driving Agility and Flexibility in Material Handling Workflows


By Daniel Theobald, CIO and co-founder of Vecna Robotics

Self-driving vehicles and their systems are driving agility and flexibility in a time of unprecedented business and labor demands. This is part two of a four-part series focused on robotic integration in the material handling value stream.

Increased customer expectations are affecting every part of the supply chain. People are spending an unprecedented amount of money, and they want more options and quicker service.

This is expanding the range of inventory, increasing inventory turnover rates from days to hours, and changing expectations from free two-day to free within the hour delivery. 

The only way to meet these expectations is for the manufacturers, suppliers, distributors, and logistics partners to create flexible and agile workflows.


A mixed fleet of intelligent self-driving vehicles is one way to increase dexterity and elasticity. They can complete physically demanding jobs, work uninterrupted for multiple shifts, and smarter robots have the freedom to adapt to changes without human assistance. However, they are only one part of the solution.

Ultimate flexibility and agility come from the ability to change the operational process based on current circumstances, without increasing costs or sacrificing quality, safety, or rate of delivery.

This can be achieved by avoiding rigid methods, delivery routes, resources (robot, human, legacy operation), or allocation of resources for warehouse activities. Operations managers should look at all available resources, routes, and methods and pick the most efficient combination to optimally perform the given task.

This allows operations to seamlessly adapt to surges in demand, unexpected changes, rapid delivery requirements, and the vast stock keeping unit (SKU) proliferation brought on by the rising consumer expectations.

“The Amazon Effect”

Often called the “Amazon Effect”, customers, all customers, want what they want, when they want it. A report by Drop-Off (a last-mile delivery service solution) found 43 percent of consumers expect “much faster” delivery, 31 percent expect same day delivery, 65 percent will switch to companies that match Amazons delivery options, and 79 percent will not make a repeat purchase if the first experience involves a damaged product.

In addition, history shows customers want more product variety. When Walmart tried to cut a mere 15 percent of their “slow movers” (infrequently ordered items), consumers publicly voiced their outrage. This led to a decrease in customer satisfaction and a substantial decline in sales, forcing Walmart to restock the retired units.

This proves customers value quality, variety, and expedited delivery. This forces logistic entities to adopt a continuous fulfillment schedule and keep larger inventories to address consumer demand.

Balancing increased demand and delivery expectations

In the past, material handling operations increased labor to handle SKU surplus and faster delivery. However, this is no longer a viable option for three main reasons:

  1. There are not enough workers available. The material handling industry is facing the largest labor shortage in its history, struggling to fill 183,000 new roles a year.
  2. It is not financially sustainable. Material handling wages have doubled in the past five years. This, paired with incremental hiring, training, turnover, and benefit costs make it impossible for organizations to remain competitive utilizing only human labor.
  3. It is not safe. Humans should not be placed in the physically and mentally taxing working conditions these roles demand.

During this labor crisis, autonomous vehicles can be a cost-efficient method to meet customer expectations without sacrificing service/product quality or employees’ wellbeing. Mechanized helpers automate the mundane, repetitive, and often dangerous tasks non-stop without getting tired or slowing down.

However, to be valuable investments, self-driving vehicles need to do more than drive, lift, pull, load, or pick. As Albert Einstein said, “The measure of intelligence is the ability to change.”

Thus, intelligent self-driving vehicles need to come with a level of autonomy that allows them to adapt to changes in demand, avoid obstacles, and work carefully with and around people and other automation systems. A Vecna Robotics’ customer reported their autonomous vehicles encounter unplanned obstacles up to 90 percent of the time.

If they required human assistance every time, it would negatively affect production and increase non-value-added travel. Vecna Robotics’ systems overcome this using the unique Vecna Autonomy Stack with several key features:

  • Multi-modal sensors that fuse together for high confidence navigation
  • Dynamic obstacle avoidance technology that allows robots to make the safest choices while working alongside people
  • Topological reasoning to find the best way to complete each mission
  • Local decision-making to establish true autonomy and ensure work gets done even when the unexpected occurs

The best autonomous solution is not simply a self-driving vehicle, but a self-driving vehicle paired with the best autonomy to adapt to change as it occurs.

vecna pallet jack copy
A Vecna Pallet Jack maneuvering around static and moving obstacles. © Vecna Robotics

The power of learning

Another shared aspect of agility and flexibility is the ability to learn, to understand new, more effective ways to work as environments shift.

The logistics market is set to grow to $12.5 billion by 2022. This growth will affect the way logistic operations are managed and run. It is imperative robots stay relevant and adapt capabilities to meet new and fluctuating business requirements.

Vecna Robots keep track of their activities and challenges. This information is analyzed by Vecna’s Beacon service and fed back into the fleet, updating the robots’ abilities and operation’s value stream in real-time.

Organizations can constantly track the current state of operations, identify additional areas of waste (operational inefficiencies), analyze the effects of change, and implement optimal improvements continuously (Figure 1).

The service allows organizations to quickly reconcile with rapidly changing fulfillment requirements and creates a constant cycle of improvement.

Vecna_Value Stream Graphic-01 (002) copy
Figure 1: Value Stream

The power of transparency

Many distribution centers, 3PLs (Third Party Logistics), and manufacturing production plants produce more than 60 percent of their product in the fourth quarter to meet seasonal demand. In the past, organizations had to recruit, hire, and train temporary workers.

Vecna Robotics offers a mixed fleet of vehicles from pallet jacks to tuggers, picking systems, conveyors, and stackers with the ability to communicate and share information with each other.

This means what one robot in a fleet knows, all robots in the fleet knows; what one robot learns, all robots learn. Instead of incurring the hiring costs of temporary staff, whose average wage has nearly doubled in the last five years, warehouse teams can quickly bring in new robots or repurpose existing ones between zones and even across warehouses.

The ability to learn is valuable, but the ability to share knowledge across a fleet, across an entire warehouse, is the key to staying agile at scale.

The power of teamwork

Intelligent self-driving vehicles provide the resilience and precision needed to work around the clock without diminishing the amount and quality of output. Vecna Robotics’ self-driving vehicles contain the right level of autonomy, technology, and partner services to change, learn, and evolve.

Even with enhanced navigation and intellect, autonomous self-driving vehicles are only a portion of the solution. Set workflows cannot handle fluctuating fulfillment needs. Workflows should be malleable to shifting changes in operational needs, resources, and goals.

Vecna’s is the world’s first orchestration engine, designed to evaluate all available work that needs to be accomplished, evaluate all available agents (diverse types of robots, human workers, or other equipment), and dynamically optimize task allocation among the robots. tracks real-time information collected by the self-driving vehicles, agents, and other systems. It allows for power management and opportunistic charging, traffic management, performance monitoring, real-time adjustments to shifting priorities or unexpected errors/delay, and optimal distribution of tasks based on current operational status.

The orchestration allows multiple types of robots, humans, and legacy automation to work as a team. maximizes the efficiencies of every agent and uses real-time data to increase the efficiency of the entire operation.

vecna dream team
The dream team: Vecna Robotics Retriever working with a mobile Conveyor at the DHL Challenge. © Vecna Robotics


Autonomous solutions are a necessary component of today’s warehouse and value stream. However, not all autonomous vehicles are created equal.

Sustained competitive advantage derives from a solution that is always working, learning, sharing, adapting, and evolving as operations, customers, and the world changes.

Daniel Theobald, CIO and co-founder, Vecna Technologies
Daniel Theobald, Vecna Robotics CIO and co-founder

About the author: Daniel Theobald co-founded Vecna Technologies in 1998, with the mission of empowering humanity through transformative technologies. He’s been at the forefront of robotics R&D for over 20 years, partnering with DARPA, DoD, NASA, NIH, USDA and many others.

Today, he is the Chief Innovation Officer of Vecna Robotics. Vecna Robotics supplies Automated Material Handling, Hybrid Fulfillment, and Workflow Optimization solutions featuring mobile robots powered by a unique learning autonomy stack and the world ’s first orchestration engine,

Theobald is co-founder and President of MassRobotics and holds a bachelor’s and master’s degree in Mechanical Engineering from MIT. He has received the Henry Ford II Scholar Award, NSF Fellowships, and a Hertz Fellowship award.