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How can you troubleshoot feedback algorithms for robots with redundant sensors?

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Feedback algorithms are essential for robots to perform tasks that require sensing and acting on the environment, such as navigation, manipulation, or exploration. However, feedback algorithms can also be prone to errors, especially when robots have redundant sensors that provide overlapping or conflicting information. How can you troubleshoot feedback algorithms for robots with redundant sensors? In this article, you will learn some tips and techniques to identify and resolve common issues that affect robot control and feedback algorithms.

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Syeda Shabih Zehra Hamdani

Project Engineer | Tech Lead | Asset Integrity Engineer| Field Robotics | Prototyping | Mechanical Engineering
Dr. Daher Sayfeddine

Ph.D. (Robotics), D.Cert. CMI LEVEL 8, MEng.(Mechatronics & Int. Engineering), CMgr. FCMI, CEng MIET, PMP?, PRINCE2?…
Saksham B.

Electrical Engineering @ Georgia Tech | Founder Stayive & Gadgenics

1 Identify the problem

The first step to troubleshoot feedback algorithms is to identify the problem that you are facing. Is your robot behaving erratically, inconsistently, or inaccurately? Is your robot unable to complete the task or achieve the desired goal? Is your robot experiencing sensor noise, drift, or failure? To answer these questions, you need to observe your robot's performance, collect data from its sensors and actuators, and compare it with the expected output and behavior. You can use tools such as logging, debugging, visualization, or simulation to help you with this step.

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Syeda Shabih Zehra Hamdani

Project Engineer | Tech Lead | Asset Integrity Engineer| Field Robotics | Prototyping | Mechanical Engineering
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One very efficient way found after real time troubleshooting of sensors feedback algorithm is to isolate each sensor from the main system and check the output from each sensor individually. Fine tuning of sensor can only be made by testing the output of the sensor in different condition and applying different constraints one by one along with analysis each response. This method not only highlights the discrepancies in sensor response to a constraint but also highlight keep adjustment parameters in the feedback algorithm.

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Dr. Daher Sayfeddine

Ph.D. (Robotics), D.Cert. CMI LEVEL 8, MEng.(Mechatronics & Int. Engineering), CMgr. FCMI, CEng MIET, PMP?, PRINCE2?, PMI-ACP?, PM LEVEL 6, PSM I?
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every problem has features/patterns that can be characterized/ classified/ described. once that is done 90% of the problem is solved as the sources of this patterns will be shortlisted.

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Steven Mcgough

Championing Embedded Technology | LinkedIn Top Voice | Passionate about Tech| Sparking Innovation for Future-Ready Solutions
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Troubleshooting feedback algorithms in robots with redundant sensors starts with problem identification. Observe the robot for erratic, inconsistent, or inaccurate behavior. Check if it fails to complete tasks or achieve goals. Look for sensor issues like noise, drift, or failure. Collect and compare data from sensors and actuators against expected outcomes. Use tools like logging, debugging, visualization, or simulation for analysis. This step is crucial for understanding the underlying issue, allowing for targeted solutions to improve the robot's feedback system.

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Gerard Kinneen

Helping Businesses who support people with ADHD | Your Destination for EdTech and HealthTech Solutions | How can our mental health Marketplace help you?
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I first isolate and test each sensor individually to identify any discrepancies in their data. Then, I analyze the algorithm's logic to ensure it correctly prioritizes and integrates inputs from these sensors, adjusting for any redundancies. This method helps pinpoint inaccuracies and optimize the overall sensor feedback system for reliable performance.

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Akash Jaiswal

??Top Robotics Voice | Innovator | Embedded System | Robotics?? | R&D | HWUD
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Spot on! Troubleshooting feedback algorithms starts with a precise problem identification. Whether it's erratic behavior, inconsistency, or sensor issues, keen observation and data analysis are key. Utilizing tools like logging, debugging, visualization, or simulation enhances the process, enabling a thorough examination of your robot's performance.

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2 Analyze the data

The next step is to analyze the data that you collected from your robot and its sensors. You need to look for patterns, anomalies, or discrepancies that can indicate the source of the problem. For example, you can plot the sensor readings over time, calculate the error between the actual and desired state, or compare the data from different sensors. You can also use statistical methods, such as mean, standard deviation, correlation, or regression, to quantify the quality and reliability of your data.

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Saksham B.

Electrical Engineering @ Georgia Tech | Founder Stayive & Gadgenics
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The article rightly guides troubleshooting redundant sensor feedback algorithms. For clearer understanding, it could emphasize systematically analyzing data, including visualizing sensor readings over time and employing statistical methods for effective problem identification.

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Dr. Daher Sayfeddine

Ph.D. (Robotics), D.Cert. CMI LEVEL 8, MEng.(Mechatronics & Int. Engineering), CMgr. FCMI, CEng MIET, PMP?, PRINCE2?, PMI-ACP?, PM LEVEL 6, PSM I?
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as part of fault detection and isolation, it is advisable to develop mechanisms for detecting faults in individual sensors. Implement algorithms that can identify when a sensor is providing unreliable data. Once a fault is detected, isolate the problematic sensor and switch to an alternative if available.

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3 Isolate the cause

Once you have analyzed the data, you need to isolate the cause of the problem. You can use techniques such as hypothesis testing, experimentation, or elimination to narrow down the possible factors that affect your feedback algorithm. For example, you can test different hypotheses by changing one variable at a time, such as the sensor configuration, the feedback gain, or the algorithm parameters. You can also eliminate potential causes by disabling or replacing some sensors or components and observing the effect on your robot's performance.

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Sayyida K

Senior AI & Robotics Engineer |Mobile robot | Robot manipulator |ROS | ROS2 | Perception | C++| Autonomous navigation | ADAS| Algorithm| SLAM | Git
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1. Iterate Testing and Analysis: Repeat testing and analysis iteratively. Refine your hypotheses based on new information obtained during the process. 2. Utilize Diagnostic Tools 3. Use Redundancy or Alternatives

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4 Fix the issue

The final step is to fix the issue that you have isolated. You can use different methods depending on the nature and severity of the problem. For example, you can calibrate or synchronize your sensors to improve their accuracy and consistency. You can also adjust or optimize your feedback algorithm to account for sensor noise, redundancy, or uncertainty. You can also implement fault detection and recovery mechanisms to handle sensor failure or degradation.

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5 Test and validate

The last step is to test and validate your solution. You need to verify that your feedback algorithm works as expected and that your robot performs the task correctly and reliably. You can use metrics, such as accuracy, precision, robustness, or efficiency, to measure your robot's performance. You can also use scenarios, such as normal, extreme, or unexpected, to evaluate your robot's behavior. You can also repeat the previous steps if you encounter new or unresolved problems.

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Dr. Daher Sayfeddine

Ph.D. (Robotics), D.Cert. CMI LEVEL 8, MEng.(Mechatronics & Int. Engineering), CMgr. FCMI, CEng MIET, PMP?, PRINCE2?, PMI-ACP?, PM LEVEL 6, PSM I?
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Data Validation and Calibration: Ensure that all sensors are calibrated correctly and provide accurate measurements. Check for any discrepancies or outliers in sensor data. Implement data validation techniques to filter out erroneous readings.

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6 Learn and improve

The final step is to learn and improve from your troubleshooting experience. You can use feedback loops, such as reflection, feedback, or adaptation, to enhance your knowledge and skills. You can also use documentation, communication, or collaboration to share your findings and solutions with others. You can also use best practices, standards, or guidelines to improve your feedback algorithm design and implementation.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you troubleshoot feedback algorithms for robots with redundant sensors?

1

2

3

4

5

6

7

1 Identify the problem

2 Analyze the data

3 Isolate the cause

4 Fix the issue

5 Test and validate

6 Learn and improve

7 Here’s what else to consider

Robotics

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How can you troubleshoot feedback algorithms for robots with redundant sensors?

1

2

3

4

5

6

7

1 Identify the problem

2 Analyze the data

3 Isolate the cause

4 Fix the issue

5 Test and validate

6 Learn and improve

7 Here’s what else to consider

Robotics

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