WiBotic Software Package Improves Energy Management for Robot Fleets

WiBotic announced the launch of Commander, an energy management software package designed specifically for large fleets of robots. Commander is a platform with the goal of optimizing the energy supply of drones or any battery-powered robot employing WiBotic’s charging technology. The software library package provides API to control battery parameters.

In an interview with EE Times, Ben Waters, CEO and co-founder at WiBotic, pointed out that the adoption of robots is growing, and various organizations are investing heavily in their charging systems. Waters explained how one of the biggest challenges was designing the system to be simple and flexible while also scalable and highly secure.

“The goal of WiBotic Commander is to provide software tools for robot operators to better understand, and then optimize, the delivery of power to heterogeneous fleets of robots,” Waters said. “The software will provide reports that show where, when and how much energy is being used by a robot fleet regardless of the type of robot or battery. This will allow operators to physically move charging stations, change the schedule for charging, or change charge parameters such as maximum voltage and current delivered to the battery, to make their robots more productive (reducing the number and cost of robots) and to make the batteries in those robots last longer.”

Figure 1: Commander API (Source: WiBotic). Click to enlarge the image.

Energy optimization
WiBotic’s wireless charging system enables fully autonomous charging of drones, so they can be constantly on standby, or repeatedly fly, without the need to replace the battery manually or mechanically. Such use allows robot fleet owners to optimize flight times even without the presence of an operator.

Providing a comprehensive view of the charging infrastructure, including a visualization of the availability and status of charging, and historical information on which charging systems are used more than others is a goal of the new software package, Commander. Operators can determine the optimal positioning of the charging platform to maximize opportunities for drone activity.

“For mobile robots, the problem is often that the contact charging stations are too bulky to be placed in the area where the robots operate. The robots therefore must leave that area to go to a charging station — taking them out of service for long periods of time.  Better placement of charging systems and using smaller and unobtrusive wireless chargers allows the robots to charge while remaining in the works space — during short pauses for instance or as they are loaded and unloaded,” said Waters.

Figure 2: Charge Data (Source: WiBotic). Click to enlarge the image.

Waters pointed out how for drones the problem is more acute since their relatively small batteries discharge very quickly. Typical flight time for a drone is 30 minutes or less, meaning its range is limited to the distance it can fly in 15 minutes so it has enough charge to return home.

“With the recent easing of autonomous flight rules, drones can now fly from charging station to charging station — vastly extending their range.  However, they must know the status of the next charging station before they take off, lest they arrive to find another drone taking their landing spot or a charging station that is out of service. Drone operators must have confidence that the charging infrastructure is in place to complete a long-range mission before applications such as powerline or railroad inspections can truly become autonomous,” commented Waters.

The key is to implement proactive charging techniques that leverage technical data to improve battery energy. “So, instead of always charging every battery to its maximum voltage level, and at the maximum possible speed (current) — which is what most chargers do – operators can now use only as much energy as is needed to complete the job.  For instance, if the battery will run the robot for 12 hours, and the work shift is only 8 hours, there is no reason to charge the battery to 100%. By stopping at 95% you may extend battery life by 50%,” said Waters. He added, “the same goes for the charge current.  If the robot is offline overnight for 12 hours, there is no reason to charge the battery in 1 hour.   Commander can reset the charge rate for that robot, and every robot in its group, to charge more slowly but still be ready the next morning.”

energy management
Figure 3: Map View of Charging Stations (Source: WiBotic). click to enlarge the image.

Software package
With Commander’s features and API, Waters highlighted how you can increase the lifetime of expensive lithium batteries, collecting and storing every log file from every battery charge that occurs across a fleet of robots.

“This log file contains valuable data on the battery (i.e. how it accepts energy during the charge and how long charging takes) as well as information on the charging station (i.e. which stations are available right now and which stations are historically being used more than others),” said Waters. He added, “this information can be used to redesign the charging infrastructure to make charging more available to more robots — especially in ‘opportunity charging’ scenarios where they need to get a quick charge many times per days.  The data can also be used to monitor battery performance to identify battery failures before they occur or to benchmark performance across different brands of batteries.  This data is also important for the growing demands of regulations around the battery and charging safety.”

Users can set a pattern to charge quickly during the day when the robot’s uptime is critical, and more slowly at night to maximize overall battery life.

Waters said, “At its core, Commander is a communication mechanism and database for gathering and storing information across a network of charging stations. In today’s networking world, it’s important for that architecture to be as flexible as possible. Our software team recognized this and developed Commander as a ‘Docker Container.’  This means it is a stand-alone application that can run on just about any computing device from a Windows laptop to a dedicated Linux server to even something as simple as a Raspberry Pi.  Because of this architecture, Commander can also be hosted in the cloud with data collection occurring across a global network of transmitters over the internet. Or, it can be hosted on an internal server that uses a secure local area network to communicate with transmitters within a single facility.”

Commander can also be used for environments where IT security is crucial, but it can also be ported to any cloud using the docker RESTful container API.  All data seen in Commander can be accessed by calling the API even from external systems to automatically access and act on the collected information. The user interface provides direct visibility into the status of all parameters and allows users to adjust charging settings and perform system maintenance such as firmware updates.  “For instance, the warehouse management system can recognize when a robot has 10 minutes of downtime and can ask for the status of the nearest WiBotic transmitter.  If available, it can send the robot to that station for a quick charge – and it can even adjust the charge voltage and speed (current) for that charge cycle if desired,” said Waters.

WiBotic anticipated that Commander will be used in all those applications where densely clustered fleets of robots are required within a single facility, “as we expand Commander’s capabilities, we will explore its ability to also collect charging data directly from “smart” batteries or from the robot’s operating systems.  This will allow the software to eventually incorporate robots that are not using WiBotic hardware,” said Waters. Waters commented that over time we could expect wider adoption across dispersed robot networks where only one or two robots may be at each location, but where there are hundreds of global locations. Security robots, inspection robots and delivery robots are examples of those applications that will also benefit from better management of charging infrastructure.

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