10 real world robot deployment challenges
Have you ever wondered what it takes to deploy a mobile robot in the real world? What are the challenges? What are the key considerations? What are the factors that can completely derail the mission?
In this article, we will explore some of the key real world robot deployment challenges that need to be considered when deploying a mobile robot.
Table of Contents
- Challenge 1: Safe mobile robot navigation
- Challenge 2: Harsh environmental conditions
- Challenge 3: Reliable Communication
- Challenge 4: Data management and privacy
- Challenge 5: Hardware failures
- Challenge 6: Software failures
- Challenge 7: Power management
- Challenge 8: Social acceptance
- Challenge 9: How many is too many robots?
- Challenge 10: Ethical, legal and social implications
- Key takeaways
Challenge 1: Safe mobile robot navigation
One of the biggest challenges with deploying a mobile robot is ensuring that it can safely and effectively navigate its environment. This can be a difficult task, as there are many potential obstacles that the robot could encounter, such as:
- Other robots
- Uneven terrain
While some of these obstacles are static (i.e., do not change their position over time), others like the humans are highly dynamic and often unpredictable. It is quite a challenging task for a robot to dynamically adapt to unforeseen situations. For instance, on the first encounter of the stairs, the robot needs to be able to figure out that if it keeps going forward, it will likely tumble down the stairs damaging itself and possibly the surroundings.
Challenge 2: Harsh environmental Conditions
On a similar note to the safe navigation challenges, harsh environmental conditions also pose a challenge. Often times, the robot needs to rely on its sensors to be able to perceive the environment and figure out where it is and where to go next. But, what if the conditions are such that the sensor(s) is (are) rendered utterly useless?
Consider driving in heavy rainfall or through a snow or sandstorm. For us humans, it is quite a challenge and safety risk as is owing to reduced visibility, imagine a robot trying to do this autonomously using sensors like Cameras or Lidars.
Consider another scenario where a robot is deployed in a room on fire, a fire fighting robot scenario. The suspended soot particles and the cloud of smoke can easily render the camera useless making it hard for the robot to operate in such dirty, dangerous and dull environments.
Challenge 3: Reliable Communication
Given the scale of the task, sometimes it is efficient to deployment multiple robots to accomplish the task as opposed to a single robot. Alternatively, given the limited on board computational power, a robot would likely need to acquire and send the sensor data to be processed elsewhere, such as a powerful base station.
Either way, there is a need for reliable communication be it with peers, based station or a centralized cloud. However, as with any wireless communication, there are a number of potential problems that could occur, such as:
Interference from other wireless devices
Poor signal due to obstacles in the environment (e.g., walls, furniture, etc.)
Lack of coverage in certain areas (e.g., inside a metal storage container)
- Bandwidth limitations
- Slow communication leading to delayed response from the robot
These issues can lead to communication problems and potentially pose a safety risk if the mobile robot is not able to receive critical commands or transmit important data. Hence, there is a need to consider such communication challenges and prepare the robot to be as self-resilient and resilient as possible.
Challenge 4: Data management and privacy
To navigate safely, the mobile robot needs to have some form of data about its environment. This data could come from a variety of sources such as apriori knowledge about the environment or acquired in real time using sensors. Either way, this poses a privacy concern.
Furthermore, the data generated by the mobile robot (e.g., sensor readings, pictures, etc.) is often stored locally on the robot. However, this data needs to be transmitted to a remote location (e.g., base station, cloud) for analysis and processing. This again raises privacy concerns as this data is being transmitted over the network where it could potentially be intercepted by third-party entities. Hence, there is a need to consider data privacy and security when deploying a mobile robot.
Challenge 5: Hardware failures
Like any machine, mobile robots are susceptible to hardware failures. This could include:
Power system failures
Such failures can lead to the mobile robot becoming stranded or stuck in its environment and pose a safety risk.
Challenge 6: Software failures
In addition to hardware failures, mobile robots can also experience failures. This could include:
These types of failures can often be more difficult to recover from, as they can result in the mobile robot becoming lost or stranded.
Challenge 7: Power management
Another key challenge is power management and energy efficiency. Mobile robots need to be able to operate for long periods of time without needing to be recharged. To do this, they need to be energy efficient in their movement but current batteries used to power up such robots often limit operational abilities. Ignoring onboard power management can lead to a complete mobile robot immobilization during its mission.
While there is a need to develop new energy sources that can power robots for longer periods of time, until then, smart on-board power management can help increase the possibility of task completion. Some unconventional methods such as solar power, hydrogen etc. are being investigated and deployed but they are yet to become mainstream power source for the commonly available robot platforms.
Challenge 8: Social Acceptance
A mobile robot will also need to be accepted by the humans in its environment. This could be a challenge if the robot is perceived as a threat or if it is not considered to be trustworthy.
To be accepted, the mobile robot needs to be designed in a way that is perceived to be safe and trustworthy. This could include having a friendly appearance, using soothing tones, etc.
Challenge 9: How many is too many robots?
Another key challenge is regulating the number of mobile robots in a given environment. If there are too many robots, they could potentially interfere with each other, induce unwanted redundancies, or, even create a safety hazard. If there are not enough robots, the task at hand might not be completed in a timely manner. Hence, there is a need to consider the number of robots to deploy for a given task and also how to regulate their behavior.
Challenge 10: Ethical, legal and social implications
When deploying a mobile robot, there are also ethical, legal and social implications that need to be taken into account. These include:
Is the robot hacking-proof and tampering-proof?
What data will be acquired and logged by the robot?
Who has access to the data and is there any identifiable information?
What are the risks associated with the deployment of the robot?
Can the robot be misused for unethical practices?
What are the risks associated with the deployment of the robot?
How will the mobile robot be financed?
Who is liable for damages if a robot causes damages?
Is the use of the robot compliant with local, national and international laws?
How will the robot impact humans?
How will the robot impact the environment?
What are the potential benefits of the deployment of the robot?
How will the deployment of the robot affect the social order?
How will the mobile robot be integrated into the existing infrastructure?
There is no easy answer to these questions, but they need to be considered before deploying a mobile robot.
As you can see, there are many challenges that need to be considered when deploying a mobile robot in the real world. By taking these challenges into account, you can increase the chances of success for your mobile robot deployment. Deploying multiple robots as a team or even a swarm comprising thousands of robots might sound easy but in fact comes with a whole set of challenges on top of the aforementioned deployment challenges.