Robotics MATLAB Projects - MATLAB Solutions

• Problem & Objective: Implement real-time wall-following navigation controllers for a 2-wheel differential drive mobile robot using 8 sonar range sensors on a real-time target platform.
• Key MATLAB Functions: sim, controllerDifferentialDrive, readSonar, plot
• Expected Output/Metrics: Wall standoff distance tracking error (<2 cm), trajectory smooth curvature plot, real-time loop execution rate (100 Hz), and sonar noise filtering response.

• Problem & Objective: Develop a 2D kinematic indoor mobile robot simulator in MATLAB to benchmark path planning algorithms (A*, PRM, RRT) and obstacle avoidance behavior in user-defined maps.
• Key MATLAB Functions: binaryOccupancyMap, plannerAStar, plannerPRM, show
• Expected Output/Metrics: 2D indoor grid map plot with planned path overlays, path computation time (ms), total trajectory length (m), and collision-free clearance margin.

• Problem & Objective: Solve inverse kinematics and trajectory planning for a 7-DOF surgical robotic arm guiding skew-line needle insertion for high dose rate brachytherapy tumor targeting.
• Key MATLAB Functions: rigidBodyTree, inverseKinematics, fmincon, show
• Expected Output/Metrics: Target needle placement RMS accuracy (<1.0 mm), 3D needle trajectory plot, joint limit avoidance verification, and tissue force profile.

• Problem & Objective: Model thermodynamic phase expansion dynamics of liquid nitrogen pressurized vessels powering artificial pneumatic muscle actuators in mobile field robotics.
• Key MATLAB Functions: sim, simscape.Value, step, plot
• Expected Output/Metrics: Actuator force-contraction characteristics, pressure vessel temperature/pressure curves, energy density comparison (J/kg), and force control bandwidth.

• Problem & Objective: Develop an integrated telemetry and control GUI dashboard for a wireless vacuum-adhesion wall-climbing robot to monitor motor currents, tilt angles, and suction pressure.
• Key MATLAB Functions: uifigure, sim, pidtune, uialert
• Expected Output/Metrics: Real-time sensor readout GUI dashboard, motor speed step response curves, safety adhesion loss alert trigger, and telemetry latency.

• Problem & Objective: Create a web-accessible MATLAB tele-laboratory framework allowing remote engineering students to compile and execute motion control models on physical Lego mobile robots.
• Key MATLAB Functions: legoev3, readRotation, start, stop
• Expected Output/Metrics: Web interface control responsiveness, robot encoder trajectory tracking error, live video stream frame rate, and remote command latency.

• Problem & Objective: Build a 18-DOF dynamic hexapod robot walking model in Simscape Multibody, designing tripod/wave gait pattern generators and joint servo PID torque controllers.
• Key MATLAB Functions: smimport, sim, pidtune, smwrite
• Expected Output/Metrics: 3D multibody animation of tripod gait, leg joint torque profiles (N-m), center-of-mass trajectory stability, and walking speed (m/s).

• Problem & Objective: Model multi-fingered dexterous robot hand grasp dynamics, tuning impedance/force controllers to accomplish stable object manipulation in simulation and hardware.
• Key MATLAB Functions: rigidBodyTree, simscape, sim, solveIK
• Expected Output/Metrics: Finger contact force trajectories (N), object grasp stability region, joint angle kinematics plots, and grasp success rate (>95%).

• Problem & Objective: Implement autonomous crop-row navigation, weed detection image segmentation, and Bluetooth telemetry steering control for a mobile farming robot.
• Key MATLAB Functions: imbinarize, purePursuit, bluetooth, write
• Expected Output/Metrics: Crop-row detection centerline extraction mask, vehicle heading error (<2 degrees), weed detection recall (>92%), and row-following accuracy.

• Problem & Objective: Simulate multirotor UAV package delivery mission profiles incorporating wind disturbance rejection, battery energy constraints, and 3D waypoints obstacle avoidance.
• Key MATLAB Functions: uavScenario, waypointTrajectory, readUAV, sim
• Expected Output/Metrics: 3D flight trajectory plot, delivery time latency, battery SOC energy consumption (Wh/km), and landing accuracy (<0.5m).

Sample MATLAB Implementation: 2-DOF Robot Arm Inverse Kinematics

Solving joint angles (Theta1, Theta2) for target end-effector coordinates (x, y):

% Link Lengths
L1 = 0.5; % Length of Link 1 (m)
L2 = 0.4; % Length of Link 2 (m)

% Target End-Effector Position
x_target = 0.6; y_target = 0.3;

% Inverse Kinematics Calculation (Law of Cosines)
D = (x_target^2 + y_target^2 - L1^2 - L2^2) / (2 * L1 * L2);
theta2 = atan2(sqrt(1 - D^2), D); % Elbow-up solution
theta1 = atan2(y_target, x_target) - atan2(L2 * sin(theta2), L1 + L2 * cos(theta2));

fprintf('Joint Angle 1: %.2f degrees\n', rad2deg(theta1));
fprintf('Joint Angle 2: %.2f degrees\n', rad2deg(theta2));

Frequently Asked Questions (FAQs)