Chapter 5 • Theory & Derivations

Mobile Robotics, Localization and Mapping

Comprehensive university textbook unit covering fundamental principles, governing relationships, and engineering applications of Mobile Robotics, Localization and Mapping.

§5.1 Differential-drive kinematics

**OpenSTEM Mechanical Engineering · Book 12: Robotics and Automation · Unit 5: Mobile Robotics, Localization and Mapping.** Educational draft. All worked numbers are illustrative unless stated otherwise; do not use the calculations alone to certify a physical robot or protective system.

§5.2 Wheel odometry and pose integration

§5.3 Inertial and visual sensor fusion

§5.4 Occupancy grids and mapping uncertainty

§5.5 Localization failure and recovery

THREE WORKED QUESTIONS

Step-by-Step Robotics and Automation Solutions

Three original questions connect calculations, definitions and interpretation. Open each solution to follow the reasoning.

Solved Problem Example 5.1: Calculation & Verification: Differential-drive kinematics

Problem Statement: For vR=0.60 m/s, vL=0.20 m/s and track b=0.50 m, body speed is 0.40 m/s and yaw rate 0.80 rad/s. Reproduce the substitution on paper, carry units through each stage and check the scale with an independent estimate. Precision in displayed decimal places does not demonstrate precise knowledge of link lengths, accelerations, friction coefficients or camera calibration. If inputs are rounded or synthetic, the outputs inherit those limitations; do not label them as measured robot performance.

Worked Engineering Derivation:

**Boundary Cases audit.** Check a zero-input limit, a typical operating point and a maximum planned input. Where derivatives exist, estimate local sensitivity to a 5% change. If the result changes sharply, prioritize a measurement of the sensitive parameter rather than increasing numerical precision elsewhere. Extend the example by sweeping one independent input through a realistic range. Predict the qualitative trend before computing. Then change another input in a separate run; explain why changing both simultaneously would make causal interpretation weaker. Document any singular, discontinuous or saturating regime instead of hiding it by clipping a plot without explanation.

Solved Problem Example 5.2: Calculation & Verification: Wheel odometry and pose integration

Problem Statement: An engineering practitioner analyzes a mechanical system governed by **Wheel odometry and pose integration** under steady operational loading.

Worked Engineering Derivation:

Left travel 0.40 m and right travel 0.50 m imply nominal center travel 0.45 m between readings. Reproduce the substitution on paper, carry units through each stage and check the scale with an independent estimate. Precision in displayed decimal places does not demonstrate precise knowledge of link lengths, accelerations, friction coefficients or camera calibration. If inputs are rounded or synthetic, the outputs inherit those limitations; do not label them as measured robot performance. **Discretization audit.** Choose a simulation step that resolves the fastest physical phenomenon of interest. Check convergence with a smaller step and confirm that numerical artifacts do not explain apparent stability or contact behavior. Sampling rates must exceed the bandwidth of the phenomena they are claimed to detect. Extend the example by sweeping one independent input through a realistic range. Predict the qualitative trend before computing. Then change another input in a separate run; explain why changing both simultaneously would make causal interpretation weaker. Document any singular, discontinuous or saturating regime instead of hiding it by clipping a plot without explanation.

Solved Problem Example 5.3: Calculation & Verification: Inertial and visual sensor fusion

Problem Statement: An engineering practitioner analyzes a mechanical system governed by **Inertial and visual sensor fusion** under steady operational loading.

Worked Engineering Derivation:

A residual gyro bias 0.1°/s accumulates about 6° heading error over one minute if uncorrected. Reproduce the substitution on paper, carry units through each stage and check the scale with an independent estimate. Precision in displayed decimal places does not demonstrate precise knowledge of link lengths, accelerations, friction coefficients or camera calibration. If inputs are rounded or synthetic, the outputs inherit those limitations; do not label them as measured robot performance. **Uncertainty audit.** Differentiate precision from accuracy: repeated values near one another may share a systematic offset. Use replicated trials and a calibration reference, and consider correlations when combining uncertainties. An error bound must be linked to a defined operating range. Extend the example by sweeping one independent input through a realistic range. Predict the qualitative trend before computing. Then change another input in a separate run; explain why changing both simultaneously would make causal interpretation weaker. Document any singular, discontinuous or saturating regime instead of hiding it by clipping a plot without explanation.

Solved Problem Example 5.4: Calculation & Verification: Occupancy grids and mapping uncertainty

Problem Statement: With prior occupancy 0.50, detection probability 0.80 and false-positive rate 0.20, a positive report yields posterior occupancy 0.80. Reproduce the substitution on paper, carry units through each stage and check the scale with an independent estimate. Precision in displayed decimal places does not demonstrate precise knowledge of link lengths, accelerations, friction coefficients or camera calibration. If inputs are rounded or synthetic, the outputs inherit those limitations; do not label them as measured robot performance.

Worked Engineering Derivation:

**Traceable Verification audit.** Record firmware or model version, sensor calibration, test fixture revision and all rejected trials. Set acceptance thresholds before viewing the final traces. If a physical trial cannot be carried out safely, use simulation only and write the missing validation item explicitly. Extend the example by sweeping one independent input through a realistic range. Predict the qualitative trend before computing. Then change another input in a separate run; explain why changing both simultaneously would make causal interpretation weaker. Document any singular, discontinuous or saturating regime instead of hiding it by clipping a plot without explanation.

Solved Problem Example 5.5: Calculation & Verification: Localization failure and recovery

Problem Statement: An engineering practitioner analyzes a mechanical system governed by **Localization failure and recovery** under steady operational loading.

Worked Engineering Derivation:

For planar errors 0.12 m and 0.05 m, Euclidean position error is 0.13 m. Reproduce the substitution on paper, carry units through each stage and check the scale with an independent estimate. Precision in displayed decimal places does not demonstrate precise knowledge of link lengths, accelerations, friction coefficients or camera calibration. If inputs are rounded or synthetic, the outputs inherit those limitations; do not label them as measured robot performance. **Dimensional Balance audit.** Perform a units check by substituting SI base units and showing both sides match. For angles, state that trigonometric functions expect radians unless explicitly converted. For probabilities, check output within [0,1], and for lengths or times reject negative values when the model defines only positive quantities. Extend the example by sweeping one independent input through a realistic range. Predict the qualitative trend before computing. Then change another input in a separate run; explain why changing both simultaneously would make causal interpretation weaker. Document any singular, discontinuous or saturating regime instead of hiding it by clipping a plot without explanation.