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Types of Mobile Robots – What to use where?

Mobile robots are capable of locomotion, they move around their environment and are not fixed to one physical location. They can be classified in two different ways; by the environment wherein they work and by the device, they use to move.

Let’s discuss different examples of different environments wherein mobile robots can work:

  • Underwater robots or autonomous underwater vehicles (AUVs) which can direct themselves and travel through water. AUVs are also called as Swimming Robots.
  • Aerial Robots are autonomous micro air vehicles, specializing in their guidance and control in the air.
  • Land-based robots categorized as wheeled robots, tracked robots, and legged robots. These are more complex types of robots and are autonomous humanoid as it requires many degrees of freedom and synchronization. Also known as unnamed vehicle group (UGVs), they navigate on inside the house or dry land.
  • Delivery & Transportation robots can move materials and supplies through work with the capability of moving around by navigating through an uncontrolled environment with or without the need for the physical or electro-mechanical guidance system.

Mobile robots can be autonomous or non-autonomous, in order to do the achieve motion, it relies either on guidance devices such as sensors or physical devices that allow them to travel a pre-defined navigation route in relatively controlled space.

Hence the two types of mobile robots are:

  1. Non- Autonomous guided mobile robots
  2. Autonomous mobile robots

Non – Autonomous Mobile Robots:  Guided mobile robots or non-autonomous mobile robots require some sort of guidance system or instruction to make a movement that allows them to travel pre-defined navigation maps in a controlled environment. The pre-defined navigation map such as magnetic tape, bar codes, wire or sensors installed on the environment’s floor that creating an inflexible environment.  These are the following types:

  1. Autonomous Guided Vehicle (AGV): This AGV requires the external guidance system in the form of magnetic strips to travel. These follow a rigid form of the preset route. Typical AGV applications incorporate transportation of raw materials, work-in-progress, and finished goods in support of manufacturing production lines, and storage/retrieval or other movements in support of picking in warehousing and distribution applications. AGVs provide automated material movement for a variety of industries including Automotive, Food & Beverage, Chemical, Hospitals, Manufacturing, Pharmaceutical, Paper.
  2. Rail Guided Vehicle/Cart (RGV/RGC): RGV/RGC is a fast, flexible and easily installed material transport system that travels at a predefined path guided by rails or tracks. RGC has separate input/output stations that allow it to perform multiple operations at once. These mobile robots are an efficient, cost-effective and fast option for complex sorting applications.
  3. Guided Fork-lifts: This specific AGV type is inspired by the conventional human manned forklifts. These forklifts are becoming increasingly complex and intelligent full of autonomy for some applications. These could manned/unmanned traveling with the help of external devices such as tablets, human, etc. The forklift AGV is designed to provide both horizontal and vertical movement of the load.

Autonomous Mobile Robots: Autonomous mobile robots (AMR) are just like humans; can make their own decisions and then perform tasks accordingly. Autonomous robots can perceive their environment and remember it. Based on this info they navigate in a controlled environment without any predefined path or electro-magnetic guidance map, that way they offer flexibility to a large extent. AMRs also optimize the travel distance by calculating the shortest path for every mission & drive efficiency in the warehouse.

Let’s look into a few of its applications:

  1. AMR for Good-to-picking: This includes robots bringing mobile shelf units filled with items to a workstation. In this case, pickers remain at their workstations while software-driven AMRs deliver shelves with different materials directly to the order pickers’ workstation.
  2. Picking Assist Autonomous Mobile Robots: In this case, the robots travel to pick locations, where operators deliver (“pick”) goods based on the robot’s needs. They are an AMR base with an operator interface that provides information about picking order. The robot tells the operator “I want this item and here is where you can find it”. The user interface is also interactive, being possible to provide further info about the product or receiving info from the operator such as “picking accomplished”.
  3. Unmanned Aerial Vehicles (UAVs): These are basically drones moving large products through the air in distribution centers with the help of RFID-scanning technology to offer real-time inventory visibility in the warehouse. Guided autonomously by remote control, UAVs can sense their environment and navigate on their own.
  4. Sorting Robots: These robots play an important role in high speed sorting esp in fulfilment centers. These robots work on a mezzanine with chutes/rabbit holes for location or order positions. Sortation is easily achieved by utilizing a fleet of sorting robots that sort the orders by dumping them through chutes/rabbit holes. The dropped orders or parcels are collected in sacks, gaylords or containers, which will be shipped directly to customers.

Now, along with commercial and industrial sectors, mobile robots are a common sight in public sectors such as hospitals and airports as well. With the evolution of advanced navigation systems & enhanced safety features they are only a step away to become human allies in our everyday activities.

Functional Challenges of Mobile Robots

Over the past few years, mobile robots have started emerging as one of the most important assets in industries for material handling and other intra-logistics operations. These robots have minimized the need for manual handling and an increased number of handling tasks. Little do people realize that even though these robots carry heavy loads but still face functional challenges that are not often noticed and have adverse effects on their maneuverability.

Challenges Synoptic

Mechanical Design Overview

The design of mobile robots capable of intelligent motion and action involves the integration of many different bodies of knowledge. The aim of this system is to idealize an existing autonomous mobile robot, on all levels. This includes the mechanics, kinematics, dynamics, perception, sensor fusion, localization, path planning, and navigation. All these aspects must be reviewed and modified to a modular system if necessary new modular modules must be designed and developed. This way a robust and modular autonomous mobile robot, capable of intelligent motion and performing different tasks will arise.

Mechnical Design Overview

The major challenges include mechanical structure, navigation, and human-centred intelligent control, of which navigation is the most challenging functionality required for such autonomous systems. The navigation comprises four dominant blocks of competencies: perception, localization, cognition and motion control.

  • Perception is the ability of a robot to interpret meaningful data from its sensor,
  • Localization defines how good a robot determines its position in the environment,
  • Likewise, Cognition and Motion control helps in extracting a way to achieve its goal and modulating the motor controller to reach the desired trajectory.

Of all the above four competencies in navigation, localization is considered the most challenging area which requires the greatest research attention.

localization-mobile robot

A Pitfall to Mobile Robots

Assuming one could just attach a GPS sensor to a mobile robot that could solve the localization problem informing the robot of its exact position in the environment. Unfortunately, the current GPS system is not practical with accuracy to say several meters which are almost unacceptable for localizing the mobile robot. Furthermore, the current advancements with positioning technologies are not proving any place in the market especially when it comes to indoors or in obstructed areas. Also, localization is not just limited to determining an absolute pose in space, rather a series of collaborative tasks like building a map, then identify the robot’s relative pose with respect to mapping. In other words, one can say that the robot’s sensors play a crucial role in the localization and the sensor’s inaccuracy and incompleteness contributes to major challenges in localization.

In perception, the major contributor lies with sensor noise and aliasing, further aggravating the problem of localization. On the other hand, using a noise-free sensor alone can’t solve these challenges of insufficient information to identify robot’s pose in the world, instead, it also requires robot programming to recover the robot’s position over time based on series of sensor readings.