Questions related to Mobile Robotics
What's the best method to calculate the distance between a mobile robot's position and the boundary of a fixed obstacle using Matlab?
The functionalities of other robot may include mapping, perception, and navigation.
I have placed IMU MPU2950 on an AMR (Autonomous Mobile Robot) with a metallic body. Even though I am using Madgewick Filter to smooth out the data, it is not enough and confuses the localization algorithm in the AMR. Is there any way to dampen the vibrations with physical additions?
I am currently interested in autonomous construction vehicles. Specifically I am looking at the model and Control of crawler loaders. So if you could recommend any books or articles on the topic or have any tips, please post them here.
Has anyone (in the community of rover path planning and rover motion estimation) used commercial wheeled mobile robots in their research?
I am working on mobile robots formation control. I have some issues in choosing linear and angular velocities for the leader robot and follower robots. The results are changing for different velocity parameters. I would like to know, How to choose Linear velocity and Angular Velocities for mobile robots in leader-follower-based formation control methods?
Hi, a friend wants to publish an article related to the mobile robot navigation slam algorithm. Could someone please suggest a few journals with low impact factor?
I am pursuing my masters in Mechatronics (Germany) and currently working as a system validation intern. I am looking for some advice/guidance on possible topics in the field of autonomous driving. I am open to any sub-field but my current experience is in system validation of ADAS/ Autonomous Driving mostly in a Software-in-Loop environment. There is currently not a industry accepted standard for validation of ADAS/AD features so something along these lines would be greatly appreciated
Thanks in advance!
I'm currently working on a new improvement for the artificial potential field algorithm (APF) for obstacle avoidance, I've got some interesting results in ensuring a local-minimum-free algorithm with a low computation cost; In order to show the effectiveness of my algorithm I have to compare it with other methods, specifically the Harmonic potential functions which are well-known for overcoming the local-minimum problem.
Hence, I need the opinion of researchers who have experience with this method for both theoretical and practical aspects.
We would like to validate and test our multi-robot algorithms with some research-platformed mobile robot. Are there recommendations to buy some small mobile robots to test our multi-robot algorithms? The mobile robots are supposed to be inexpensive but they are easy to be configurated with some sensors.
I am looking for the benchmarks that can be used to compare obstacle avoidance algorithms? what is the norm that will decide the efficiency of obstacle avoidance algorithms is higher or lower? What types of graphs or trajectory plot will help to decide the performance of the algorithm?
Thanks in advance.
I'm doing some research in swarm robotics and for testing algorithms and learning about them a swarm simulator will help me.
Please share your last trends of the combination between legged and underwater mobile robot in terms of leg design and kinematics
I some papers, the mean square error is considered. In some other, the mse is normalized by dividing the error by the (total sampling instants x the total length of the reference trajectory).
Which solution does represent the factual error?
I am working on the human following robot. the robot extracts a feature of clothes's texture and distinguishes between the people that they stand up in front of the robot. So, the robot needs that it will be robust and fast.
I am currently investigating means to assess human interaction interest on a mobile robotic platform before approaching said humans.
I already found several sources which mainly focus on movement trajectories and body poses.
Do you know of any other observable features which could be used for this?
Could you point me to relevant literature in this field?
Thanks in advance,
- path planning robot simulation .
- 3D map environment model / robot workspace.
- mobile robot will autonomously navigate.
I have a mobile robot with 600 W (rated power) and I need to implement a PV system on the robot to be completely solar-powered. I want to reduce the size of panels and get the required power.
The robot dimensions 110cm x 80 cm.
I am looking for narrowing down the topic for my master theses. Real industrial problems to be solved with innovative technologies are the most interesting topics.
In your paper Large-scale 3D printing by a team of mobile robots, a "rotor/stator pump" is being used to deliver the mixed cementitious material to the nozzles attached to the robots.
What exactly is the type of mechanism inside the pump? Is it progressive cavity/eccentric screw, diaphragm, or another type of positive displacement pump?
I want to develop neuro fuzzy controller for mobile robot. I know how to use anfis toolbox in matlab. I can replace the existing PID-fuzzy controller with anfis controller but it gives same output responce. There are two main issues I faced. 1. anfis only works well for same kind of input it is trained for. For instance, if step input of fuzzy pid was 5, anfis would work well for only step input of 5, not for others. 2. How to improve the performance of anfis controller developed from fuzzy pid. I have studied the anfis matlab help, some books but could not get practical simulation help. . Thanks in anticipation
In "Simultaneous Stabilization and Tracking of Nonholonomic Mobile Robots: A Lyapunov-Based Approach", the authors stated that the nonholonomy of mobile robots allows control of the system with less control inputs. A mobile robot is underactuated in nature, and it's often controlled with less number of control inputs than the system's degree of freedom (if dynamic is ignored). How does the nonholonomy of the system helps with that?
I want to make practical experiments for visual SLAM, and I want a simple method for the ground truth other than using Laser Range Finder of another synchronized camera.
we know that path planning for mobile robot is one of the most fundamental and complex problems in robotics. PDEs ( partial differential equations with variable exponents ) have been used in a variety of science areas, such as Mechanics, Calorific, Image processing, Image restoration, Electrorheological ﬂuids and so on. Hence we want some references in these areas!
I want to extract data from object detection sensor in Matlab 2018 (Mobile Robotics Simulation Toolbox). This data is the display vector array form of dimension (1x3) range; angle and label. I want to use this data for object avoidance controller using fuzzy logic. When I use demux to split this data into three elements, I get error “Simulink cannot propagate the variable-size mode from the output port 1 of 'dynamicModelPID/Object Detector' to the input port 1 of 'dynamicModelPID/Demux'. This input port expects a fixed-size mode. Examine the configuration of 'dynamicModelPID/Demux' for one of the following scenarios: 1) the block does not support variable-size signals; 2) the block supports variable-size signals but needs to be configured for them “
I have tried using different blocks for this purpose but still I get same error. I could not find out proper solution of this problem. Any knows about it
Recently, I met a young researcher that insisted on the statement that position control for mobile robotics (ground and aerial) is already solved with many working solutions and that the real research lies in the estimation (pose estimation), specially in UAVs. Do you agree with this statement?
If not, please write bellow the reasons you think that there is for the continuity of mobile robot motion control research. Which areas there are for improvement? What are the technical reasons for continuing researching these solutions?
I am currently designing a deformable wheel for a six-wheeled lunar vehicle and I am trying to model the trafficability of this wheel on a lunar surface. To do this I am using Bekker’s Equations.
My question: I found normalized DP (drawbar pull) values of 26 for a wheel with grousers and a value of 0.48 for the same wheel, but without grousers. The value of 26 seems very high based on results I have found in other papers online so I am skeptical of my results and need help confirming that the assumptions and calculations I made make sense. I have attached a .pdf that walks you through what I did and assumptions I made. Along with this I highlighted areas where I am uncertain as they may be possible areas of error.
Thanks again for your time and any advice relating to this will be very helpful since this is my first time working with Bekker's equations and wheel-soil interactions in general.
Note: the soil characteristics I used were the recommend ones found in the Lunar hand guide
I want to implement fuzzy logic control (Fuzzy PID) system in Matlab for tracking control of differential drive mobile robot. I will combine Fuzzy logic with Neural network in future .Does anyone know any simulator for this purpose? I have seen SimIam simulator by Georgia tech university USA, but I could not find its documentation, help or any tutorial. I need help, if anyone has experience with this simulator (SimIam) or any other simulator that can be used with Matlab in Windows system (not ROS)?
A Mobile robot Simulator compatible with Python (scikit-fuzzy) is also okay.
I'm doing a paper on mobile robots for my school, it's a litterature review on the existing technologies, some history and future perspective, and I need some articles to read, I was hoping to get some help finding good ones,
Thank you in advance,
Given a Fractional Order PID controller designed for trajectory control of mobile robot. The question is How to implement it using one of the arduino platforms knowing that when approximating the fractional integrator and derivative using discrete transform it gives infinite orders of terms in the Z-domain.
We have many different algorithms for map building and localizing a mobile robot in 2D space. In case of 3D space (open) to fly ariel vehicle, we use GPS to know the location longitude, latitude, altitude, etc. However, GPS is not suitable for the closed environment. Sometimes environment with many building or cloudy atmosphere is not suitable for using GPS. How can we localize (know the X, Y, Z coordinates) for Ariel vehicle in a closed environment?
Currently, My PH.D. Student and I using a differential Drive Mobile Robot to control it using Active Disturbance Rejection Control, We used two PMDC motors for the two wheels. But, the problem is that when we went to the data sheets to get the parameters of the PMDC motor, we did not find anything related to these parameters, like resistance, inductance, and inertia. Anybody can help us to measure these parameters experimentally. or lead us to a specific type of PMDC motor with its data sheetd that are readible.
I have been working with estimating the flight altitude of Aerial robots using 3D planar SLAM from the point cloud data of an RGB-D camera. I extract the 3D horizontal planar surfaces and map them in order to localize the aerial robot in its flight altitude.
I am starting a project where I would like to achieve also the x and y-axis localization of the aerial robots. As the RGB-D sensors are noisy, extracting the vertical planes for localizing in x and y-axis, using 3D planar SLAM techniques becomes a difficult problem.
I am looking for ideas where I can combine a 3D planar SLAM algorithm with a visual SLAM algorithm in order to achieve a robust localization in unstructured and unknown environments. I would appreciate any papers or suggestion regarding this topic.
I want to control the movement of humanoid robots. will be possible if I use some control methods such as PD over Gyroscope, and by applying control methods over Gyroscope I control the movement of humanoid robots?
Which control strategy is best suitable for flight control applications in UAV(Fixed Wing/Quad-rotor etc.)? Adaptive Backstepping, MRAC, L1 Adaptive Control?
Humans are naturally quite good at controlling systems provided it can give input to the actuators via an interface (joystick etc.). In the humanoid community, motion primitives are obtained by logging human examples. Do you know any non humanoid research in which human input is logged to create motion primitives of the system it is controlling at that time?
I'm looking for INSs that can be used in underground environments. Basically, I'm interested in obtaining accurate positions x, y and attitude (roll, pitch and yaw) on which I will apply some filtering filtering algorithms (such as EKF). Clearly, using GPS units won't work underground. I have tried this MEMS IMU for testing http://www.phidgets.com/products.php?product_id=1056_0, but it's not accurate enough for my purpose. Do you guys know any company that provides what i'm looking for?
In my system, I have starting and end position of a robot. I need to find angle if robot needs to rotate and velocity of a robot. Can I get solution using kalman filter that what will be Transition matrix, x(k-1), b(k), u(k).
While doing a research I came across a diagram under the title " the tree of control methods" it depicts all major branches of control theory methods classic advanced , linear and non-linear.
The problem I just can't remember in which book I have found that , does anyone know about such diagram or at least suggest to me another similar list ?
In my research, my topic is localization based on 4-Mecanum Wheels AGV
so, i try to reserch reducing slippage between ground surface and 4 wheels
but i couldn't find papers enough about such topic on google scholar
so, could you introduce related papers, researches, projects?
somebody help me to find that.
I am simulating Nonlinear MPC for nonholonomic mobile robot. I have to create references trajectory for it as: line-shape, circular shape, and 8-shape... With model of mobile robot: input as u=(v,w) with v-velocity, w-angular velocity. output as X=[x,y,theta]. To calculate cost funtion = (x-x_ref)^2+(y-y_ref)^2+(theta-theta_ref)^2+lamda*u1^2+lamda*u2^2. If you have the sample code on matlab/simulink, you will share for me.
I am looking for the oldest publication describing the sense-plan-act paradigm known from robotics. The earliest paper I managed to find so far was Brooks' "A Robust Layered Control System For A Mobile Robot" from 1986. Yet, Brooks mentions sense-plan-act as the "traditional decomposition of a mobile robot control system into functional modules". So, we assume that there are older publications addressing the paradigm.
Any help is highly appreciated!
I am working on a project about controlling a mobile robot via USB joystick. I need a force-feedback joystick which can be programmable and (preferably) be used with Beaglebone black and Robotic Operating System (ROS).
when input is four and output two is then how to solve that problem. I have four input in left, right, front obstacle & another one is heading angle then my output is left wheel & right wheel velocity. Please tell me by graph if possible.. In my input there are three linguistic variable e.g. near, medium & far obstacle & heading angle is negative, zero & positive. Then my output velocity is slow, medium & fast..
It should cover the mobile robot navigation or neural network and fuzzy system fields, if possible? This is my first article and I'm looking for a journal with low impact factor and with a quick review process. The journal should cover mobile robot navigation, Neural network and fuzzy logic fields.
Thanks in advance.
We are seeking to understand the needs of caregivers who are providing support for their elderly loved ones. We seek to improve the quality of life of the caregiver by supporting their efforts to care for their loved ones. Our solution set is based on a fully autonomous and empathetic robotic platform. Any studies, pilots, experts and or anecdotal experiences/oppinions would be helpful in shaping our development. Thank you!
In the paper I am not able to find a reference to their code, which isn't really a problem since the dissertation "UNSUPERVISED LEARNING AND REVERSE OPTICAL FLOW IN MOBILE ROBOTICS" p.68 is referring to the reader to the code for the same exact algorithm at the address http://cs.stanford.edu/group/lagr/road_following/
Problem is that the link "only" includes 3 videos demoing the final algorithm. I'm interested in seeing and understanding the code but there's literally just 3 links to these videos.
I hope some of you can help me find the code or point me in the right direction. So far I've managed to calculate the optical flow properly and I am now looking in to finding the starting horizontal position for the template matching.
I hope it is OK to ask this question here, thank you.
What are the best simulation software and robot path planning tool under ROS environment, which can easily implement the unstructured environment. Moreover, if the path is probabilistic, then what are the best State based approaches for mobile robots.?
In motion control of mobile robots what are the major differences between Path following and trajectory tracking and stabilization about a posture , and why we use each one of them and in which cases ?!
Hello guys, I seek for an instrumentation book which focuses on mobile robot test design and measurment systems.
I've studied principles in instrumentation since I was undergraduate student. I am trying to design TestBeds mostly used loadcells. till know I've design and manufacture two of them and face many problems. I seek for design patterns and recommendations and how to use configuration of sensors and what are most important concerns.
You know when you rigid a mobile robot you make it to stand and some dynamics are changed so we seek for that?
I hope I can clear and eluminate what I think
I'm looking for a robot chassis with wheels, motors and a battery: mid-size (~70cm x 70cm), drives through grass, sufficiently fast (~5km/h) and can carry a payload of about 5kg. I'm thinking of building an autonomous robot, putting a laptop on it, connecting some usb cameras and a gps device.
Is there a kit I could buy that ticks all of these boxes and is still somewhat unexpensive? The stuff I find is either way overpriced (contains a lot of stuff I don't need) or is too small and uncapable.
Another option is building it yourself, but I don't have the experience or mechanical training. I have about 5 months to build this robot because I'm hoping it will compete in a robotics competition.
Doing dynamic model of RRRR robot manipulator, using Lagrange equation:
D(q)∗q′′+C(q,q′)∗q′+g(q)=τ , in Matlab, the issue is that, I'm getting very long-long terms, every equation is a couple of pages, I also tried to extract the inertia matrix, again very long terms are there; I reviewed my code, and try use: simplify, rewrite, combine, factor ... commands, but doesn't work. The strange thing is that, I see there are many term involving sin and cos, similar to each others, but there are staying separately.
Is potential field or navigation potential function suitable for obstacle avoidance for optimal path planning of mobile robot using optimal control approach.
I´m trying to build a cheap mobile robot, capable of doing SLAM. I have a raspberry pi with a raspicam and want to find out algorithms to extract depth from monocular cues and try to implement as much as I can in opengl es since the SBC is not very strong. I know there are solutions out there (like structure from motion and make3d) but wanted to know if anyone has already try something like this…
i develop a manual gain pid controller for mobile robot but i want the kp,ki,kd gain should control by its own and it interact with environment factor and give stable navigational motion, how i designn this in simulink ?
I'm working with autonomous UAV (quadcopters). Does anyone have any tips for setting CRIUS AIO with MegaPirate for use with QGroundControl? In systems such as the Mission Planner, there are no major problems, but the QGroundControl initial setup is a bit confusing.
Considering that a robot with an Ackerman steering, the front wheels are oriented to a different angle, I was wondering what is the best approach for estimating the robot's pose. Differential rotation you calculate the robot's position by measuring the amount of ticks for each wheel but does the same apply for Ackerman?
As per path control, I design simulink function block for unicycle mobile robot, but the gain control of pid for desired position gives some unbalanced movement of robot. Can anyone suggest how I can control the movement so accurately for unicycle mobile robot.
Let's consider the situation that convoy consists of only two vehicles, leader and follower. Leader is driven by operator, follower can detect relative position of the leader (e.g. camera based - slow and noisy). Can you recommend a good paper on this issue?