After a very successful reading of the ‘Complete guide to robot manipulators: advantages and applications’, here we provide the answers to the top 50 questions asked about mobile robot manipulators.
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Mobile manipulators are becoming increasingly important in industrial settings, providing a unique combination of mobility and precision. These robots are now used in industries ranging from manufacturing to agriculture, thanks to their ability to automate complex tasks. In this article, we answer 50 frequently asked questions about mobile manipulators, covering topics such as collaborative robotics, hazardous environments, precision engineering, and programming robot manipulators for optimal performance.
A mobile manipulator robot is the one that combines the capabilities of a mobile robotic platform (moving through multiple locations) and a manipulator arm (object manipulation). These robots have the ability to move in their environment while performing tasks such as grasping, moving, and handling objects.
Mobile manipulators have applications in various industries such as logistics, manufacturing, agriculture, inspection or the healthcare sector. They are especially useful for automating repetitive or hazardous tasks such as loading and unloading materials, assembly, handling toxic substances, or harvesting agricultural products.
Industrial robots are typically fixed in a single location and perform repetitive tasks in a controlled environment. Mobile manipulators, on the other hand, can move freely to perform tasks at different points in a dynamic environment.
Mobile manipulator robots in agriculture are used for automatic fruit and vegetable harvesting, plant pruning, sowing or crop monitoring. These robots are optimized to work in outdoor conditions and adapt to uneven terrain.
Advances in Robotnik’s mobile manipulators include more intuitive interfaces, sensors for even safer collaboration in shared environments, and Artificial Intelligence algorithms that allow them to better understand both people and the environment and make smarter decisions.
For example, through the use of high-performance batteries, more efficient path planning algorithms and power saving modes when not active. Hardware designs with low-power motors and advanced controllers also contribute in this regard.
The two basic parts are a mobile platform and a robotic arm. In addition, there is a wide variety of final tools available to attach to the arm, depending on the needs of the task: grippers, suction cups, robotic hand, screwdriver, vision tools…
They use cameras RGBD, 3D LiDAR, ultrasound, GPS, IMU or force/torque sensors to detect objects, map their environment and calculate the force needed to manipulate objects.
Robotnik’s mobile manipulators are safe. They are equipped with safety systems, sensors and advanced collision detection and avoidance algorithms to ensure safety in collaborative environments shared with humans.
Mobile manipulators typically use ROS (Robot Operating System), an open-source framework that allows integration of sensors, actuators, and complex algorithms, making it the go-to solution for mobile robotics.
The main advantage of these robots is flexibility and scalability. They can move over large areas and reconfigure to perform multiple tasks according to the need of the moment, without major modifications to the layout. It is not necessary to modify the infrastructure through which these robots will move, so scaling the number of units is easier.
Duration varies depending on use and the type of battery included, but, on average, it can last between 6 and 10 hours on a single charge.
It depends on the model. RB-VOGUI+ or RB-SUMMIT+ are some of the manipulator robots that can operate outdoors, even in variable environmental conditions such as wind, rain or uneven terrain.
Historically, the industries with the greatest use of manipulator robots are logistics, manufacturing, automotive, and the chemical/pharmaceutical industry. But the agricultural and construction sectors have considerably increased their use in recent years.
The cost varies depending on the features and capabilities of the robot, generally, the market price ranges between 50,000 and 150,000 euros, depending on the model and level of customization.
A mobile manipulator improves productivity due to its ability to work in shifts 24/7, improving productive times, avoiding repetitive tasks for workers and reducing the rate of errors/failures in the processes.
They can operate fully autonomously or semi-autonomously, depending on tasks and system configuration. They can make decisions in real time based on data from their sensors or execute the missions of an operator who is managing it remotely.
Installation can take from a few days to several weeks, depending on the complexity of the environment and application.
One of the main challenges in the mobile robotics sector is to advance in autonomous navigation issues. We have overcome important barriers in that area but there is still room for improvement. We are also working to equip our robots with greater capacity for human-robot interaction and algorithms for more complex manipulation tasks.
Yes, many are designed to work collaboratively with other robots, sharing information to optimize tasks and interact according to each one’s capabilities.
Autonomous mobile manipulation refers to a robot’s ability to move and manipulate objects without human intervention, using AI, sensors, and algorithms to make decisions in real time.
High quality sensors provide more accurate data, improve navigation and handling accuracy. Poor sensors can lead to errors and task failures. Therefore, the low price of a robot should not always be the deciding factor for the user. The cost of a robot includes, for example, the quality of the sensing it incorporates.
Artificial Intelligence in robotics is used, for example, for object recognition, trajectory planning and decision making in real time.
Yes, they can be relatively easily reprogrammed or trained to learn new tasks through Deep Learning techniques.
Not necessarily. There are intuitive programming interfaces that simplify configuration and scheduling of tasks. However, programming certain types of complex tasks may require more advanced knowledge. In any case, the Robotnik team offers advice according to needs.
They can manipulate a large number of objects of different sizes, shapes and textures. From small parts on assembly lines, screws, washers, electronic components or test tubes to 20 kg boxes in warehouses.
Always evaluate the load capacity of the arm and platform, the reach of the arm, the battery life, the type of sensors and the reliability offered by the manufacturer.
The precision of the robotic arm is influenced by force sensors, advanced vision and precise control algorithms that adjust the robot’s position and grip in real time.
They integrate making the necessary adaptations to the plant layout, connecting to management systems (MES/ERP) and coordinating them with other equipment using automation software.
Challenges include manipulating irregular objects, navigating unstructured environments, and optimizing energy usage to extend operational time.
Yes, certain models can navigate multi-level environments using ramps or elevators, allowing them to operate efficiently in complex warehouse layouts.
Yes, manufacturers like Robotnik offer custom hardware and software adaptations to meet specific industry needs, ensuring that robots can perform specialized tasks, depending on the specific needs of the client.
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Yes, some suppliers offer the option to rent robots for short-term projects or for testing before making a purchase. This is known as Robot as a Service – RaaS.
One of the biggest advantages of collaborative robotics is that it is not essential for the operator to have a great knowledge in programming or robotics. The Advanced User Interface makes it very easy to operate and control the robot.
The useful life of a mobile manipulator robot generally varies between 5 and 15 years, depending on use, maintenance and operating conditions.
They improve safety by taking on tasks that are dangerous to humans, such as moving heavy loads or working in unhealthy, toxic, or difficult-to-access environments.
Yes, a single mobile manipulator robot can work in different industries due to its ability to adapt to different tasks and environments. Their versatility allows them to perform everything from assembly in manufacturing to logistics in warehouses. Their flexible programming and ability to change tools makes them useful in multiple industries.
Advances in mobile manipulation robotics are oriented towards greater autonomous intelligence, greater human-robot interaction and the ability to perform increasingly complex tasks. We are also working so that our robots can be deployed in more and more types of environments, both indoors and outdoors.
They use navigation based on SLAM (Simultaneous Localization and Mapping) and technologies such as LiDAR, GPS and AI to detect obstacles, optimize routes and adapt to changes in the environment in real time.
Yes, with proper configuration and maintenance, they can operate continuously, except for the battery charging time that each model requires.
The type of environment affects the accuracy of the sensors and the maneuverability of the robot. For example, uneven or poorly lit terrain can make navigation and manipulation difficult, if the robot itself has not been designed to operate in those specific conditions. Both the sensorization included and the IP determined by the manufacturer must be taken into account.
Yes, it is possible and, in fact, a widely used option for applications related to inspection and maintenance, for example. In these cases, remote control is executed via desktop applications or software.
Accuracy or repeatability varies by model, but many can operate with millimeter precision. The cobots from Universal Robots, for example, range from ±0.03 mm. or ±0.05 mm.
They integrate into Industry 4.0 by connecting with cyber-physical systems, IoT, and data networks in real time, allowing them to collaborate with other smart devices.
They contribute to sustainability by optimizing the use of resources, reducing waste derived from manufacturing errors and providing certain improvements related to the sustainability of industrial processes. Here we explain more about robotics and sustainability.
Manipulation robotics allow operations that require high accuracy in areas such as surgery, assembly and advanced manufacturing.
A manipulator robot is especially useful in tasks that involve risks for operators, such as those that take place in chemical plants or radioactive areas.
They are robotic arms or mobile manipulators designed to work safely alongside humans, automating repetitive or high-precision tasks in collaborative environments.
Sectors such as automotive, medicine, electronics and manufacturing are some of those that use manipulation robotics the most to improve efficiency and precision in their processes.
Languages such as ROS, Python or C++ are the most widespread for robotics programming. In this article we go into more depth about each of them, their advantages and characteristics.
In order to have an informed debate about manipulative AI, we first need to clarify what manipulation itself entails. Manipulation is a common term in day-to-day language, but philosophers have multiple definitions for it.
Philosopher dr. Michael Klenk, who works at the TU Delft, describes manipulation as follows: ‘Manipulation is a type of influence. It is to be distinguished from rational persuasion and coercion. It falls in between. Coercion takes freedom of choice away completely, manipulation perhaps lowers it a bit.’
Klenk himself defines manipulation as ‘negligent influence'. 'Good forms of influence are accompanied by a certain care for the motives of the other person. Manipulation is negligent in the sense that it is defined by the absence of such care. The manipulating party wants to achieve a certain result, and that is all that matters.'
Dr. Tjerk Timan, who is familiar with the policy and ethics of AI through his job as policy analyst at TNO in the Netherlands, describes manipulation as a kind of strategy: ‘The manipulating party knows something that the other doesn’t and takes advantage of that.’ In other words, there is a knowledge asymmetry between the manipulator and the manipulee. ‘It has to do with subconsciousness. Manipulation entails influencing persons in such a way that they do something that they actually do not entirely agree with.’
Each of these definitions concentrates on different aspects of manipulation. Klenk looks at the role of the manipulating party, who he believes to be negligent in their influence on other people. Timan also focuses on the role of the person that is being manipulated. Manipulation can only be a successful strategy, according to Timan, when there is a certain asymmetry in knowledge or subconsciousness at play on the side of the manipulee.
Manipulation is not necessarily seen as a problem when we focus on the consequences of manipulation on the manipulee. We can also manipulate people in order to benefit them, by stimulating them to eat healthier, for example. In such cases, manipulation is referred to as ‘nudging’. Meaning sometimes somebody is better off by being manipulated.
However, we already learned that manipulation can also be defined from the perspective of the manipulating person, or, manipulator. In that case, it is the act itself or the intention behind it that matters. Who believes that the act of manipulation is undesirable as such, would reject it even when it has positive consequences. Klenk opts for this point of view: ‘When you look at the act of manipulation itself, I would say that the negligence is always a failing on the part of the manipulator.’
If there is no moral difference between AI manipulation and other forms of manipulation, why then are people so worried about it? Timan explains that manipulative AI brings a lot of new ethical questions and problems with it. For instance, manipulative AI raises questions regarding data protection and the matter of scale and scope. Timan: ‘When you use AI to manipulate behaviour, even when you do so with the best of intentions, the question remains: are you allowed to use people’s data to manipulate them?’
Another issue that Timan mentions is the risk that new problems are passed on to users, sometimes called ‘responsibilisation’. ‘Take the example of fitness trackers. AI is a useful tool to stimulate people to move more, but it can lead to a problematic narrative: “it’s your own mistake that you are in bad health, look at the data”.’
The risk that the user ends up dealing with new problems connects to a larger cultural challenge of AI and manipulation, says Timan: ‘I think that digital colonialism is the biggest cultural problem regarding manipulative AI. The influence that takes place, for example through content filtering, spreads American values, which constitutes a form of subtle, yet pervasive and hidden mass manipulation.’ American values are, for example, reflected in the kinds of topics that have priority on our social media’s news feeds.
‘On an individual level, the biggest problem is the decline of freedom of choice. Especially due to the rise of immersive technologies, such as voice activated smart-home devices like Alexa or Google Home, we lack an opt-out more and more often. We can no longer choose not to participate or not to be the subject of analysis.’
Klenk raises a similar issue. ‘One of the main reasons we use AI is to make design more user friendly. However, there is a certain tension between user-friendliness and manipulation. AI makes decisions very easy for you. It reduces complexity. But this robs you of your opportunity to think for yourself. It is in stark contrast with autonomy.’
Although manipulative AI raises many moral questions, there is nevertheless no consensus on the answer to the question what is wrong with manipulation. When we reject the act of manipulation a priori, we would need legislation to prohibit manipulative AI as much as possible. But if we only reject manipulation on the basis of its consequences, we should only tackle specific instances of manipulative AI.
In April , the European Commission published the AI Act. In this Act, the Commission proposed, amongst other things, to prohibit manipulative and exploitative AI that leads to physical or psychological harm. A prohibition would make one believe that manipulation is considered to be wrong as such. However, what actually matter in the proposed prohibition are manipulation’s consequences. Forms of AI manipulation that would do little harm are considered to be permissible under the EU’s proposed legislation.
‘The AI Act is a weird piece.’ Timan acknowledges. ‘We see that, for the first time in a long time, the Commission moves away from a form of policy that is solely risk-based. The Commission makes an odd, bold move by saying something substantial about a technology. Namely by banning certain applications.’
About the EU’s focus on harm Timan says: ‘We see that manipulation is rejected because of its consequences. That utilitarian, risk-based approach is very Anglo-Saxon. This is problematic in this case, because of the burden of proof. It’s not easy to proof as an individual that you are suffering psychological damage as a result of some hidden algorithm, on a social media platform that you voluntarily subscribed to. Moreover, most harms are long-term and cumulative. Whilst the AI Act is set up only to deal with singular instances or cases, in which a claim to harm must be based. This renders most harms due to long-term, small but incremental manipulation inadmissible.’
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