We have all seen loads of projects and publications showing mobile robots performing various logistical operations, i.e., transporting goods or passengers from one location to another. Most often these cases are either indoor or outdoor based operations. When they are outdoor operations, they tend to rely on GNSS based systems. When they are indoor cases, they are usually based on supportive infrastructure, be it built on beacons, reflectors, or stickers (or whatever you prefer). Both solutions are working like a charm most of the time when the conditions stay within the designed framework. But when the machine leaves the designated operational area or the conditions change drastically, those high-tech machines tend to turn into expensive tin cans, which will require operator assistance for survival. We love autonomous mobile robots, especially when they are bringing delicious lunches for us, but we hate tin cans.


GIM Robotics has been doing logistics solutions from the day one. Actually, we have been doing that for close to 30 years, if we count our glorious days at one of the renowned mobile robotics lab in the world since late 1980’s, in Helsinki University of Technology, later Aalto University. We did these solutions during the times when GPS signal was jumping like a crazy rabbit all over the place. We spent good money on the top-of-the-line IMUs, external supportive solutions and later turned novel industrial 2D LiDARs into 3D LiDARs with some homemade mechatronic solutions. Probabilistic robotics became our religion early on and we have not looked back ever since. When RTK-GNSS became widely available, reasonable priced good-enough IMUs were all over the place and ready-made 3D LiDARs were brought to the markets, things got so much easier.


After University days and particularly after our six years long Academy of Finland funded Centre of Excellence period, we were ready to jump on the other side of the fence and started the GIM Robotics in 2014. In 2017 our sister company Sensible 4 was founded to focus on road-based operations and had as the main target to provide Level 4 capabilities for self-driving cars. GIM Robotics has been handling other use cases, which have been ranging from marine, railways, logistics, forestry, environmental maintenance and beyond. Based on our inhouse analysis of our focus areas, we must conclude, that various logistics related projects, PoCs and feasibility studies have been our bread and butter already for many years. 


In most of the cases, we have retrofitted our clients’ machines, or tuned commercially available robotic platforms for the job. Unfortunately, those projects are protected by NDAs. However, for several years, we have been manufacturing our own logistics platforms suitable for both indoor and outdoor operations. First version, SpOv1, has been successfully operating in Paris, France on Nokia Bell Labs campus in EIT-Digital funded LMAD project, later company and the second updated version, SpOv2, has been performing pilots in various location in the larger Helsinki area (Otaniemi, Helsinki) together with various logistics companies including DB Schenker.


The newest version, dubbed surprisingly as SpOv3, has been built solely for our own usage and we have been using it for various perception system testing and full-stack optimizations in various projects like MURO and PEAMS. Basically, we wanted to have the newest and the best platform for our extensive R&D operations and especially for related position and mapping SW stack improvements and long-term validations. We want to collect tons of data from every imaginable situation and challenge our top-of-the-line localization and environmental modeling algorithms. Especially interesting topic for us is the need to survive both in indoor and outdoor environments with the same software and same sensory setup. We want to demonstrate that our solutions survive in all conditions, because we forecast that many companies will expand their logistics solutions to serve both indoors and outdoors environments. As an example, one could mention factory warehouse logistics operations taking place both inside the factory and outside on larger areas. In the future, there will be plenty of economically justifiable single machine systems serving both indoor and outdoor areas.


Our fundamental philosophy when designing solutions for our client’s logistical problems, has been to initially test the proposed machines (new or retrofitted ones) with an extensive sensory suite. That approach will give us a clear view, which perception sensors or combinations are vital for optimal (or near-optimal) performance in any particular use case including important ODD (Operational Design Domain) definitions and restrictions. We have deep knowledge of most of the imaginable sensors, including LiDARs, radars, various camera solutions etc. Naturally we integrate the usual suspects, like IMUs, RTK-GNSS and odometry info, to our standard solutions.


To get the extensive amount of data needed for algorithmic development and SW quality validation for our main offerings (GIM-Locator, GIM-Mapper, and GIM-Observer), we needed to come up with a challenging use case, which would offer us an easy way to benefit from our own SpOv3 robot and to have extensive and frequent data sets from a difficult environment including some traditional elements normally related either to indoor or outdoor environments. In our case it means, that we will have our robot traveling frequently through some GNSS-challenging and -denied areas. We were happy to notice that the route we have been walking during our lunch breaks from our HQ to nearby large shopping mall includes several long tunnels. Furthermore, it is inherently a dynamic environment due to many pedestrians and cyclist and frequent impromptu road works. It is hard to imagine better route for our purposes.


We share this short video to give the reader/viewer, an idea what is happening while the SpOv3 robot is doing its daily task, i.e., transporting our pre-ordered lunches from Sello shopping mall back to its Homebase (our HQ). Two leftmost sub-screens are point cloud visualizations, which gives the reader a clear view how the robot is advancing on its route. The upper right screen visualizes our probabilistic 3D map, which is the result from more than 15 years of intensive research and development. We can create large maps in near-real time without any extra heavy-duty computation hardware. The lower right screen video demonstrates how the LiDAR sees the environment and uses that to localize itself in respect to the recorded environmental model. It also shows how two of our guys are getting their daily exercises, while following the robot (due to current safety regulations).


GIM Robotics continues its journey to become serious player in the wider field of logistics. We do that by showing our expertise in the current and future proof-of-concepts, pilots, projects and productizations. If you want to learn more about our logistics solutions and about how SpOv3 will continue to serve us our daily lunches when springtime arrives, give us a call, use the contact form or pay us a visit. We might even put SpOv3 to run an errand and fetch you a fresh salad from Sello shopping mall.

Robotics can sure be good for your health – and for your logistics business.

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