The Robots are coming! Are you ready? Now is the time to build the (Totally Not Evil) Robot Army! This blog creates, builds, and explores the personal 'Making' of robots. Enjoy!
Welcome to the next step in creating my Totally Not Evil Robot Army! Today, we kick off our journey into the fascinating world of robotics with a simple SLAM (Simultaneous Localization and Mapping) project.
What’s SLAM?
In the world of robots, SLAM is what helps our mechanical minions make sense of their surroundings. Imagine a robot moving through an unknown environment—how does it know where it is and where the walls (or, you know, other targets) are? That's where SLAM comes in. The robot uses sensor data to map its environment and figure out its position on that map in real time.
My SLAM_play Project
My initial SLAM project is a basic 2D simulator called SLAM_play. This simulation features a simple robot equipped with an ultrasonic sensor that explores a grid-like environment. The robot moves around, detecting obstacles and marking unexplored areas as it builds a map of its world.
The robot updates its map in real time:
Grey zones represent the areas it has explored and found clear.
Green spots mark obstacles (which may or may not be future targets for…um...peaceful interaction).
Dark grey zones represent the "frontier," where the robot has reached the limits of its sensor's range and hasn’t detected anything yet.
What's Next?
This is just the beginning. As I dive deeper into SLAM, I’ll explore adding more complex sensors, like LIDAR, and even experiment with autonomous pathfinding. The ultimate goal is to build a robot army that can navigate any environment, no matter how complex…for purely benevolent purposes, of course.
For now, I'm taking small steps, but these small steps will one day become the foundation of an unstoppable (yet totally friendly) robot force.
If you’re interested in exploring the code behind this simulator, check out my public GitHub repo here: SLAM_play Repository
Lets continue the adventure of giving the machine some SLAM —one sensor at a time!
Robot Army Motto: Mapping the future, one ultrasonic ping at a time. (for now!)
Every project reaches that pivotal moment when progress halts, and the creative spark seems to fade. For Mojo5, that moment has arrived. This little robot has encountered a significant challenge in the design of its abductors. The servos have developed excessive backlash, compromising its ability to stand and walk effectively.
In an attempt to resolve the issue, I removed the servos and installed a 'static' gear to lock them in place. Unfortunately, this fix didn't fully eliminate the backlash, and the problem persists. Addressing this issue would require a major redesign, far more extensive than initially anticipated.
With a heavy heart, I’ve decided that it’s time to retire Mojo5. But as with all endings, this marks the beginning of something new. Long live Mojo6.
Welcome back to the "Totally Not Evil Robot Army" blog. In this 11th installment of the Mojo5 series, we’re going to dive into a crucial aspect of building robust quadruped robots: using more powerful batteries to drive hobby servos. Specifically, we'll explore how increasing the available amperage and voltage can significantly improve the performance of underpowered servos and the considerations needed to ensure safe and efficient operation.
The Problem with Underpowered Servos
Building a quadruped robot like Mojo5 with cheap hobby servos often leads to performance issues. Many of these servos, such as the MG995, are slow and lack the torque needed for dynamic movements. Even with a 5V power supply, these servos can become wobbly and unreliable, especially under load. This is where upgrading to more powerful batteries comes into play.
The Limitations of the Original Power Configuration
Initially, Mojo5 used a 5V 12000mAh power bank. While this power source had a high capacity, it was limited to a maximum output of 3A. Given that the MG995 servos have a stall current rating of up to 3A each, the total current demand for the robot could easily exceed 20A during peak operation. This significant shortfall in available current was a primary cause of the robot's poor performance.
Upgrading the Power Source: LiPo Batteries
Based on previous discussions and experiments, we found that using a more powerful battery can drastically improve servo performance. Upgrading to a LiPo battery with a 2200mAh capacity, 7.4V voltage, and a 50C discharge rating provides the needed boost. This battery can supply well over the 20A needed by the servos, addressing the current limitations of the previous power source.
Considerations for Over-Volting
Risk of Burnout: Exceeding the servo’s voltage rating does carry a risk of burnout. However, anecdotal evidence suggests that slight over-volting is generally safe if monitored properly. Implementing a voltage regulator could limit the current capacity, which might be counterproductive. In general voltage regulators on servo power sources are not recommended.
Separate Circuits for Different Servos: For servos with lower voltage ratings, such as the MG90 (max 6V), consider creating a separate circuit to avoid over-volting. This will add an additional circuit which can be problematic. For my experiments with Mojo5, I used the same circuit.
Practical Application: Experimenting
Initial Setup
Battery Connection: Connect the 7.4V 50C LiPo battery directly to the power bus of the PCA9685 servo driver, bypassing capacitors and regulators. This setup ensures the servos receive power directly.
Handling Large Wires: Safely connecting XT-60 battery connectors and their thick 12 AWG wires to smaller electronics is challenging. Using a bare copper PCB or prototyping PCBs with multiple copper lines can provide a more robust connection. Soldering all wires together is an ugly but space-efficient solution.
Not Recommended!
In this experiment, I took the short cut and soldered the large wires directly in to a dupont connector. The connector was connected directly to the servo bus. This is not a recommended practice! I better connection with larger wires is recommended. In this particular case, as long as all of the servo motors do not stall, then only brief seconds of +20A current would be expected. Current greater than 7A for sustained periods of time would destroy the connectors.
Experiment Results
After connecting the 7.4V battery:
Servo Performance: There was a noticeable improvement in servo actuation. The MG995 servos operated better, with no immediate burnout.
Heat Management: Monitoring the temperature of connectors and wires is crucial. Using a finger-test method (keeping fingers on components for one minute) can help identify safe current levels. If components become too hot to touch, reduce the current.
To visualize the improvement, I have embedded a short video showing Mojo5's performance with the original 5V power bank versus the upgraded 7.4V LiPo battery. Notice the difference in servo response time and stability.
Long-Term Solutions
While the initial experiments are promising, long-term solutions require more robust hardware:
Custom Servo Driver Board: Developing a servo driver board with better connectors and thicker traces can handle higher currents more efficiently. This would replace the PCA9685 board, which is not designed for high current loads.
Current Monitoring: Implementing current measurements and safety features like e-fuses can prevent overcurrent situations and protect your components.
Conclusion
Upgrading to more powerful batteries can significantly enhance the performance of underpowered servos in your DIY robots. While there are risks associated with over-volting, careful monitoring and proper hardware can mitigate these risks. As we continue to push the boundaries of DIY robotics, sharing these experiences and solutions will help us all build more capable and reliable robots.
Introduction to Mirrored Servo Control (Symmetric Control)
One of the primary challenges in developing Mojo5 was ensuring synchronized movements between the servos on opposite sides of the robot. To achieve this, we employed a straightforward yet effective approach: mirroring the servo movements by reflecting the target angles.
Technical Implementation
To implement the mirroring effect, we introduced a boolean parameter in our Servo structure to indicate whether a servo should be mirrored. The adjustment is applied directly in the servo control function.
void moveServo(const Servo& servo, int pos) {
pos = max(servo.minPos, min(pos, servo.maxPos));
int pulseWidth = map(pos, servo.minPos, servo.maxPos, servo.minPWM, servo.maxPWM);
pca9685.setPWM(servo.num, 0, pulseWidth);
if (servo.mirror) {
pos = 180 - pos; // Adjust the position if mirroring is needed
}
pos = max(servo.minPos, min(pos, servo.maxPos));
int pulseWidth = map(pos, servo.minPos, servo.maxPos, servo.minPWM, servo.maxPWM);
pca9685.setPWM(servo.num, 0, pulseWidth);
}
the following structure is used to define all the elements of the servo
struct Servo {
uint8_t num;
int minPos;
int maxPos;
int minPWM;
int maxPWM;
int minRange;
int maxRange;
int minRangePWM;
int maxRangePWM;
bool mirror; //true => adjust IK if opposite side
};
The results of this code are directly observed in the output for the Pulse Width Modulation (pwm) values that are sent to the servos. Here you can see the servo values are 'reflected' or 'mirrored', symmetrical to one another:
Mojo5 - Symmetric control - pwm values over a rectangle gait
Practical Application and Results
In our setup, the mirror effect (symmetric control) is particularly useful for maintaining symmetry in the leg movements. This approach simplifies the inverse kinematics (IK) calculations, as the same code can be used for both sides of the robot with the mirrored adjustment applied where necessary only at the servo control.
To illustrate this concept, we've embedded a short video demonstrating the addition of a leg from the opposite side of Mojo5. The IK calculations are identical, but the servo angles are adjusted by reflecting the target angles, resulting in a mirrored motion that maintains the robot's symmetry.
Insights on Mirrored Movements
Creating a mirrored movement (symmetric control) for servos is crucial for several reasons:
Symmetry and Balance: Ensuring that both sides of the robot move in a symmetrical manner is essential for maintaining balance, especially in quadruped robots. Asymmetrical movements can lead to instability and erratic behavior.
Simplified Coding: By mirroring movements, the same IK code can be reused for both sides, reducing complexity and the potential for errors. This makes the development process more efficient and the codebase easier to maintain. The servo angles are simply adjusted because all servos turn counter-clockwise and have a 0 to 180° range based on their orientation. Servos on the opposite side face differently, so this mirroring adjustment is necessary.
Consistent Gait Patterns: Symmetrical leg movements are vital for creating smooth and natural-looking gait patterns. Mirroring helps in achieving uniform step lengths and timings, which are important for the robot's locomotion.
Summary
The mirroring technique (symmetric control) we've implemented in Mojo5 represents a significant simplification in controlling symmetrical movements in quadruped robots. By introducing a boolean flag in the servo structure and adjusting the servo angles accordingly, we achieve mirrored movements without duplicating the IK code. This not only enhances the efficiency of our development process but also ensures more consistent and predictable robotic movements.
I've recently implemented an inverse kinematics (IK) solution to enhance the precision and control of robotic leg movements. Our primary experiment involved programming the leg to execute a simple rectangular movement pattern, with a focus on maintaining accuracy and consistency. Here, I will share some intriguing geometrical observations and challenges we encountered.
Intended Path and Test Setup
For this test, the robot leg will start in the (0,-130) position. Moving clockwise, It steps backward (in my case more positive, note the inverted x axis) to the (50, -130) position. Next up by 25mm to the top. At this time I use a different z position, but it is hard to see. the motion continues around in a rectangle ending at the start.
Planned path for simple gait test. starting at the center bottom
Video Analysis
In the bolow short video, the robot steps through the gait path. The leg is mounted above the table and horizontal to the table, not in a typical robot position. I have traced each step of the path, with a small dot at the end of the foot.
As seen in the video, the motion lacks the expected precision, influenced by several factors:
Fixture Stability: The fixture holding the leg is unstable, contributing to erratic movements.
Manual Marking Inaccuracy: Yellow dots indicating key positions were marked by eye, leading to imprecision.
Servo Calibration: The calibration of the servo points was approximative. At a setting meant to be 90°, the actual angle could range between 85-95°.
Geometrical Challenges: The Skew Issue
One of the more fascinating issues we observed is the skew to the left when the leg is raised vertically. This skew is likely influenced by the constraints of the 'solution space'—the range within which the actuator operates. As a result, there is a slight warping effect in the grid area over which the leg can move.
Mojo5 Inverse Kinematics - geometric skew
Implications of the Skew
Motor-Driven Distortions: The two servomotors, designed to drive the leg in specific rotational angles, do not guarantee a perfectly perpendicular alignment of the movement path. This introduces a mathematical distortion in the intended trajectory.
Impact on Gait Creation: While this skew does not necessarily hinder the robot's ability to perform meaningful gaits, it highlights an essential aspect of robotic movement—geometric imperfections inherent in mechanical and software solutions.
Further Research on the Mapped or Solution Space
The space in which the robot can operates can be understood as the geometric area or volume within which the robot can effectively reach and manipulate objects. This space is defined by the following:
Reachability: Determined by the length of the robot's arms and the range of motion of its joints. The maximum and minimum extents of each joint define the outer and inner boundaries of this space.
Compliance: In the context of SCARA robots, the vertical compliance allows for certain movements in the vertical plane within the workspace. This selective compliance helps in absorbing forces during tasks like assembly, where vertical give is beneficial.
Kinematic Constraints: Defined by the robot's mechanical design and the kinematic equations governing its movements. These constraints delineate the paths and patterns the robot can execute.
Control Resolution: The precision with which the robot's controllers can position its joints also defines the resolution within the mapped space, influencing how finely the robot can maneuver within its reach.
Certainly a very interesting area of study in robotics!
