Author Mickael Viot is marketing manager at DecaWave.
The decades-old dream of robots helping us around the house seems closer than ever. Today’s home robots may not have the human-like structure of robots from the Jetsons, but they are increasingly able to help us with unpleasant around-the-house chores. The best-known home robots vacuum or mop floors, but others are on the market that clean our pools, clear gutters, mow the lawn, flip burgers on a grill, take a look around the house when we’re out, and more.
The opportunities for custom integrators are not quite there yet, but they certainly may be on the horizon as technologies and products continue to mature. Will robots be another “thing” within an Internet of Things ecosystem? Let’s take a look at the impact of one such improving technology — location and navigation awareness.
Today’s home robots use a variety of algorithms to navigate around a room, cleaning the whole room in a back-and-forth or roundabout manner while keeping track of where they were after circumventing furniture. They also have to detect when they get close to somewhere they shouldn’t go, like to stairs, or to the end of the area that they should working in. For example, a vacuum robot turns around when reaching the end of the carpet, while a mopping robot stops before going onto the carpet.
Robots detect when they’re getting somewhere important using a variety of sensors, including touch sensors, distance sensors (similar to radar), and infrared light (for finding base stations). This enables them to detect walls as they (almost) bump into them, stairs right before they fall down them, objects in their path before they bump, and so on.
What today’s robots don’t do, however, is keep track of exactly where they are in your house. They can tell when they approach a wall, but they generally can’t distinguish two different areas of a house, or know when they go through an open door, or anything else that can’t be sensed in the moment. In other words, they can move around and react to what they sense, but their knowledge of where they are is imprecise at best. This is why it takes robots a lot of time to hook up to their base stations to recharge after running. And this is why many buyers have reported robots getting lost in their house.
Because home robots don’t know exactly where they are, they are limited in terms of the instructions users can give them. What if you want to mop the linoleum but not the laminate flooring? What if you want to mop the dining area but not to venture into the adjoining living room area, or mop the kitchen but stay out of the breakfast nook? Detailed instructions like these are impossible because today’s robots are designed to meander around doing their job, but they cannot keep track of precisely where they are — nor are they integrated into a control processor or similar system in which they could conceivably be programmed to operate on a schedule or in specific areas, such as a lighting system for example.
More precise positioning of their environments will allow robots to accomplish more sophisticated tasks, beyond today’s activities that find them bumping around a house to perform.
Need to Overcome Indoor Tracking Obstacles
The reason that today’s robots can react to what is nearby but cannot really keep track of their location around a house is that today’s technology for tracking location indoors is limited. Sensing what is nearby is easy, using pressure sensors, radar, lasers measurement, and other sensors that are well known. But tracking location requires something new.
We all know this from our smartphones. Our mapping or navigation apps can show where we are outside, but when we go in, the best of today’s apps jump our location around and are off by tens of meters. With these levels of inaccuracy, a home robot would venture too far from the kitchen into the breakfast nook, or bump into a door frame and need to back up and try again to go through the doorway.
Most indoor location technologies, especially those running on mobile devices, use one of two methods to track their locations. The first is to use radio signals to track how far they are from central base stations. This is most commonly done with Bluetooth or Wi-Fi signals, but these are inherently limited in how accurately they can be used to measure locations, because of the narrowband nature of their radio waves.
Both use relatively long radio wave signals to communicate. These radio waves don’t have distinct starts and stops, so it’s hard to use them to measure distance. Instead, most systems estimate distance based on the signal strengths they observe, which is easy to implement, but very imprecise as a way of measuring distance.
The second way that today’s systems track location is to use sensors, like gyroscopes, accelerometers and compasses to measure movement based on a known initial location. But this approach will always have errors, since no sensors are 100 percent perfect, so over time the error will result in increasing drift.
New technology is reaching market, however, that offers the promise of ultra-precise indoor location positioning. UWB (ultra-wideband) radio transmits using much shorter bursts of communication, so the radio waves can be measured precisely to determine distance, and can track a device’s location to within 5-10cm. That is accurate enough to distinguish one area of a room from another, or to get through a doorway unscathed.
Once robots can know their precise location, they will be able to distinguish clearly between any areas of the house that their owners care about. For today’s applications of mopping and cleaning, this will enable robot owners to clarify more precisely what they want the robot to do, and where.
Location Awareness May Foster More Sophistication
More importantly, as robots become more sophisticated, and carry out more complex tasks, the ability to know where they are will be increasingly important. A robot that picks things up and returns them to their place will have to find precisely where to put things. A robot that takes a picture of a door or window to confirm that everything is locked up will have to know exactly where they are in order to take the right picture. The more complicated the tasks, the more precisely the robots will have to know where they are.
Taking this one step further, as robots integrate with mobile technology and sensors, and robots can know where people are, they can be programmed to carry out actions based on when people enter or leave a room, and perhaps commanded by other home technology subsystems. Want a robot to clean a room as soon as people leave the room? That requires knowing with certainty which room people are in, which requires precise positioning. Should be floor be mopped when the dog goes outside? Or should the lawn be mowed when the children leave the house? All of these require precise location positioning.
In the coming year we will see UWB technology bring accurate location tracking to a lot of devices and appliances. Home robots, smart homes, people tracking, and other devices, will be able to use UWB to track their own, and people’s, locations around a house or office. With precise location tracking, robots can be programmed not only to work at specific places, but to work when people and other things are in specific places. This will enable robots to truly automate not only what they do but also where and when.
DecaWave’s DW1000 is a single chip, IEEE802.15.4-2011 UWB compliant, Wireless Transceiver based on Ultra Wideband techniques.