1 00:00:04,519 --> 00:00:07,880 Speaker 1: Robots roaming the aisles at Walmart. Omrich Demiro. This is 2 00:00:08,000 --> 00:00:11,399 Speaker 1: rich on Tech Daily. Walmart is expanding the use of 3 00:00:11,520 --> 00:00:14,360 Speaker 1: robots at its stores. It's something we're seeing over and 4 00:00:14,400 --> 00:00:16,959 Speaker 1: over with a lot of different companies. We saw a 5 00:00:17,040 --> 00:00:20,119 Speaker 1: robot in action at their Burbank, California store. It's a 6 00:00:20,200 --> 00:00:22,919 Speaker 1: robot from a company called Boston Nova Robotics. They're based 7 00:00:23,000 --> 00:00:25,840 Speaker 1: up in San Francisco, and its job is to roam 8 00:00:25,880 --> 00:00:29,440 Speaker 1: the store and constantly scan the store shelves to look 9 00:00:29,480 --> 00:00:32,240 Speaker 1: for out of stock items. It's also looking for missing 10 00:00:32,360 --> 00:00:35,839 Speaker 1: shelf labels and items that are priced incorrectly. And if 11 00:00:35,880 --> 00:00:37,320 Speaker 1: you look at the robot, it kind of seems like 12 00:00:37,360 --> 00:00:39,960 Speaker 1: a big floor cleaner with kind of a giant tower 13 00:00:40,000 --> 00:00:42,040 Speaker 1: coming out of the top, and it's packed with all 14 00:00:42,120 --> 00:00:45,000 Speaker 1: kinds of cameras and sensors. There's two D, three D 15 00:00:45,479 --> 00:00:48,360 Speaker 1: and LDAR, which is similar to what those self driving 16 00:00:48,400 --> 00:00:51,519 Speaker 1: cars use. And that's important because this robot works its 17 00:00:51,560 --> 00:00:54,280 Speaker 1: way around the store all by itself and yes, when 18 00:00:54,360 --> 00:00:57,280 Speaker 1: customers are present, that is the main thing. This doesn't 19 00:00:57,320 --> 00:01:00,240 Speaker 1: happen overnight when everyone leaves the store. This happens as 20 00:01:00,280 --> 00:01:03,160 Speaker 1: customers are in the store, so it can actually identify 21 00:01:03,280 --> 00:01:04,520 Speaker 1: what's out of stock. 22 00:01:04,280 --> 00:01:06,240 Speaker 2: In near real time. Here's how it works. 23 00:01:06,240 --> 00:01:09,279 Speaker 1: It roams the aisles and it takes photos of every 24 00:01:09,360 --> 00:01:12,199 Speaker 1: shelf and every aisle as it moves along. It takes 25 00:01:12,240 --> 00:01:14,679 Speaker 1: a lot of pictures and it stitches them all together, 26 00:01:14,800 --> 00:01:17,080 Speaker 1: but also has these super bright lights on it, so 27 00:01:17,120 --> 00:01:19,520 Speaker 1: it kind of bathes the store shelves in these bright 28 00:01:19,600 --> 00:01:21,080 Speaker 1: lights so it can see everything properly. 29 00:01:21,160 --> 00:01:21,720 Speaker 2: It's kind of weird. 30 00:01:21,720 --> 00:01:24,600 Speaker 1: It looks like a giant wand going across the shelves. Now, 31 00:01:24,640 --> 00:01:28,560 Speaker 1: all these pictures become giant panoramic pictures that are terabytes 32 00:01:28,600 --> 00:01:31,400 Speaker 1: of data that's sent to computers to be analyzed. And 33 00:01:31,440 --> 00:01:34,480 Speaker 1: the idea here is that basically Walmart can identify which 34 00:01:34,520 --> 00:01:37,160 Speaker 1: items are out of stock and then they kind of check, okay, 35 00:01:37,240 --> 00:01:39,360 Speaker 1: is that item on its way? Do we have more 36 00:01:39,440 --> 00:01:40,920 Speaker 1: on the top shelf or do we have more in 37 00:01:40,959 --> 00:01:43,880 Speaker 1: the back, and then they can restock items faster than ever, 38 00:01:44,040 --> 00:01:46,200 Speaker 1: and they can also get an idea of real time 39 00:01:46,240 --> 00:01:48,960 Speaker 1: stock numbers. They also get a real time idea of 40 00:01:49,000 --> 00:01:51,680 Speaker 1: how much stock they have, and they can also identify 41 00:01:51,720 --> 00:01:54,760 Speaker 1: issues with pricing and labels in near real time as well. 42 00:01:54,800 --> 00:01:57,560 Speaker 1: This all solves several pain points for customers, like how 43 00:01:57,560 --> 00:01:59,040 Speaker 1: annoying is it when you go to a store in 44 00:01:59,080 --> 00:02:01,520 Speaker 1: an item you want is stock. So more retailers are 45 00:02:01,560 --> 00:02:04,200 Speaker 1: letting you check stock online before you go into a store, 46 00:02:04,320 --> 00:02:06,280 Speaker 1: or even reserve items online. 47 00:02:05,960 --> 00:02:06,440 Speaker 2: To pick up. 48 00:02:06,640 --> 00:02:08,520 Speaker 1: So this could really help out with all of that 49 00:02:08,560 --> 00:02:10,519 Speaker 1: in the future. Right now, the robots are part of 50 00:02:10,560 --> 00:02:13,320 Speaker 1: a test pilot, but they can scan an entire store 51 00:02:13,360 --> 00:02:15,919 Speaker 1: in a day, one hundred and fifty thousand items. They 52 00:02:15,919 --> 00:02:17,800 Speaker 1: do a bunch of aisles in an hour, but they 53 00:02:17,840 --> 00:02:20,240 Speaker 1: do need to be recharged after a few hours of work. 54 00:02:20,320 --> 00:02:24,040 Speaker 1: Now there is the big question, is this replacing humans? 55 00:02:24,040 --> 00:02:25,680 Speaker 2: That's the question I always get from folks. 56 00:02:25,919 --> 00:02:29,079 Speaker 1: Walmart, of course says it's not, but they say it's 57 00:02:29,120 --> 00:02:31,800 Speaker 1: helping them now. Usually a human worker has to go 58 00:02:31,840 --> 00:02:33,519 Speaker 1: through and do all of this manually. It's kind of 59 00:02:33,560 --> 00:02:35,520 Speaker 1: a repetitive process. They go through the aisles, they have 60 00:02:35,560 --> 00:02:38,040 Speaker 1: one of those kind of scan guns, they check the stock, 61 00:02:38,080 --> 00:02:40,440 Speaker 1: and they identify the problem areas. But the robot can 62 00:02:40,440 --> 00:02:43,280 Speaker 1: do all of this much more frequently and it's automatic. 63 00:02:43,400 --> 00:02:46,680 Speaker 1: So Walmart says this frees up to humans the associates 64 00:02:46,680 --> 00:02:48,680 Speaker 1: in their stores to bring the stock to the aisles, 65 00:02:48,680 --> 00:02:51,560 Speaker 1: put it on the shelves, fix those pricing issues or 66 00:02:51,560 --> 00:02:53,040 Speaker 1: put those items back in their. 67 00:02:52,880 --> 00:02:55,120 Speaker 2: Place, and also help customers. Now. 68 00:02:55,160 --> 00:02:57,880 Speaker 1: Watching the robot do its work was pretty mesmerizing folks 69 00:02:57,880 --> 00:02:59,200 Speaker 1: in the store that I was seeing. 70 00:02:59,320 --> 00:03:00,919 Speaker 2: You know, they just have people in the stores. 71 00:03:00,919 --> 00:03:03,320 Speaker 1: They were all taking pictures kind of selfies with the robot, 72 00:03:03,680 --> 00:03:06,120 Speaker 1: wondering what it's doing. I think Walmart should put some 73 00:03:06,160 --> 00:03:09,600 Speaker 1: sort of sign somewhere explaining what this robot's doing, because 74 00:03:09,639 --> 00:03:11,000 Speaker 1: lots of people just think it's cleaning the. 75 00:03:11,000 --> 00:03:12,320 Speaker 2: Floors, but it's doing much more. 76 00:03:12,840 --> 00:03:16,280 Speaker 1: Walmart tested this technology in a few stores in Arkansas, Pennsylvania, 77 00:03:16,280 --> 00:03:19,320 Speaker 1: and California. Apparently they liked what the robots were doing enough, 78 00:03:19,360 --> 00:03:22,760 Speaker 1: so they've expanded to fifty stores now, including the location 79 00:03:22,960 --> 00:03:26,720 Speaker 1: we saw in Burbank. There's also locations in Lancaster, Palmdale, 80 00:03:26,760 --> 00:03:29,520 Speaker 1: and Santa Clarita using the robots. That's just in the 81 00:03:29,560 --> 00:03:32,200 Speaker 1: SoCal area, but there's other states as well. If this 82 00:03:32,240 --> 00:03:34,880 Speaker 1: works out and Walmart sees big benefits from these robots, 83 00:03:34,920 --> 00:03:37,480 Speaker 1: this could be a huge rollout. Walmart has over eleven 84 00:03:37,560 --> 00:03:39,920 Speaker 1: thousand stores, and they know the competition is heating up. 85 00:03:39,960 --> 00:03:42,880 Speaker 1: There are so many delivery services out there, like Amazon 86 00:03:42,920 --> 00:03:46,000 Speaker 1: and even Walmart's own in store pickup, which this could 87 00:03:46,000 --> 00:03:48,000 Speaker 1: be a big benefit for Here's the deal. 88 00:03:48,360 --> 00:03:49,280 Speaker 2: The robots know. 89 00:03:49,360 --> 00:03:52,280 Speaker 1: Exactly where everything is in the store, so Walmart could 90 00:03:52,320 --> 00:03:55,520 Speaker 1: use that information to lead customers right to specific products 91 00:03:55,560 --> 00:03:57,720 Speaker 1: faster than ever. They also know when they're in stock. 92 00:03:57,760 --> 00:04:00,000 Speaker 1: Now keep in mind humans have been doing this forever. 93 00:04:00,080 --> 00:04:01,880 Speaker 1: When I worked it off as depot many years ago, 94 00:04:02,000 --> 00:04:04,480 Speaker 1: part of our training was to know where every single 95 00:04:04,560 --> 00:04:07,080 Speaker 1: product in the store was and in what aisle they 96 00:04:07,080 --> 00:04:08,800 Speaker 1: were in. So when a customer asked, hey, where are 97 00:04:08,800 --> 00:04:10,880 Speaker 1: the rubber bands boom, you could tell them which aile 98 00:04:10,920 --> 00:04:12,840 Speaker 1: they were in. So I guess in the future we're 99 00:04:12,840 --> 00:04:14,800 Speaker 1: going to be asking robots where things are. 100 00:04:15,120 --> 00:04:16,080 Speaker 2: I can even see. 101 00:04:15,880 --> 00:04:18,040 Speaker 1: A time in the future when you enter a store, 102 00:04:18,320 --> 00:04:21,839 Speaker 1: you want an item and a little tiny robot leads 103 00:04:21,880 --> 00:04:23,440 Speaker 1: you to the exact product you want. 104 00:04:23,480 --> 00:04:24,479 Speaker 2: Wouldn't that be crazy? 105 00:04:25,000 --> 00:04:27,359 Speaker 1: You can see the video of the Walmart robots in 106 00:04:27,440 --> 00:04:30,200 Speaker 1: action just go to my website rich on tech dot tv. 107 00:04:30,279 --> 00:04:33,000 Speaker 1: If you like this podcast, please rate and review it 108 00:04:33,040 --> 00:04:36,200 Speaker 1: in the Apple Podcasts app that way more people can 109 00:04:36,240 --> 00:04:36,760 Speaker 1: discover it. 110 00:04:36,800 --> 00:04:37,640 Speaker 2: Thanks so much for listening. 111 00:04:37,680 --> 00:04:39,880 Speaker 1: I'm rich Demiro rich on tech dot TV. 112 00:04:40,120 --> 00:04:41,040 Speaker 2: I'll talk to you real soon.