SLAM (Simultaneous Localization and Mapping) MCQs December 22, 2025August 10, 2024 by u930973931_answers 40 min Score: 0 Attempted: 0/40 Subscribe 1. What does SLAM stand for in robotics? (A) Simultaneous Learning and Mapping (B) Sequential Learning and Mapping (C) Simultaneous Localization and Mapping (D) Spatial Localization and Mapping 2. Which type of sensors are commonly used in SLAM for mapping? (A) Camera and LIDAR (B) GPS and Accelerometer (C) Microphone and GPS (D) Thermometer and Barometer 3. What is the primary goal of SLAM in robotics? (A) To create a map of an unknown environment while simultaneously keeping track of the robot’s location within it (B) To learn from previous experiences in a known environment (C) To optimize power consumption during navigation (D) To communicate with other robots in a fleet 4. Which algorithm is commonly used in SLAM to estimate the robot’s pose? (A) Genetic Algorithm (B) Kalman Filter (C) Ant Colony Optimization (D) Gradient Descent 5. What does “loop closure” refer to in the context of SLAM? (A) The process of connecting two separate maps (B) The technique to close a door in a mapped environment (C) The detection of a previously visited location to correct the map and pose estimates (D) The final stage in path planning 6. Which of the following is a challenge typically faced in SLAM? (A) Communication bandwidth (B) Battery life (C) Robot speed (D) Sensor noise 7. What is “particle filter” used for in SLAM? (A) To reduce noise in sensor data (B) To simulate multiple possible robot positions (C) To map the environment in 3D (D) To smooth the final map 8. In SLAM, what is “data association”? (A) The method of associating battery levels with navigation decisions (B) The act of sharing data between robots (C) The technique for associating GPS coordinates with map locations (D) The process of linking sensor data to specific map features 9. Which of the following methods is used for feature extraction in Visual SLAM? (A) Fourier Transform (B) SIFT (Scale-Invariant Feature Transform) (C) Laplace Transform (D) Discrete Cosine Transform 10. What does the term “odometry” refer to in SLAM? (A) The use of a map to navigate (B) The process of updating the robot’s map (C) The measurement of distances between objects in the environment (D) The use of sensors to estimate the robot’s change in position over time 11. Which SLAM method is best suited for environments with few distinct features? (A) Visual SLAM (B) Acoustic SLAM (C) LIDAR-based SLAM (D) GPS-based SLAM 12. In SLAM, what is the primary purpose of a map? (A) To communicate with other robots (B) To control the robot’s speed (C) To measure the robot’s battery level (D) To represent the robot’s environment for navigation 13. Which of the following is a key advantage of using LIDAR in SLAM? (A) Low power consumption (B) High accuracy in distance measurement (C) Color detection capability (D) Compact size 14. What role does “sensor fusion” play in SLAM? (A) Selecting the most efficient sensor for the task (B) Combining data from multiple sensors to improve localization and mapping accuracy (C) Filtering out irrelevant sensor data (D) Merging maps from multiple robots 15. What is the main purpose of “EKF” (Extended Kalman Filter) in SLAM? (A) To increase the speed of map generation (B) To simplify the mapping process (C) To reduce the number of particles in a particle filter (D) To handle non-linear models in SLAM 16. Which SLAM technique is most suitable for a small indoor robot with limited computational resources? (A) Direct SLAM (B) Graph-based SLAM (C) Particle Filter SLAM (D) EKF-SLAM 17. What is the significance of “map optimization” in SLAM? (A) Reducing the size of the map (B) Improving the accuracy of the map and the robot’s pose estimation (C) Speeding up the mapping process (D) Integrating multiple maps into one 18. Which type of SLAM is typically used in self-driving cars? (A) Visual SLAM (B) Magnetic SLAM (C) Acoustic SLAM (D) LIDAR-based SLAM 19. What does “ROS” stand for, which is commonly used in SLAM? (A) Randomized Operating System (B) Real-time Operating System (C) Robotic Optimization System (D) Robot Operating System 20. In SLAM, what is a “landmark”? (A) A distinct feature in the environment used for localization and mapping (B) The starting point of the robot (C) A point of interest in the map (D) A sensor used in mapping 21. Why is loop closure detection important in SLAM? (A) It corrects drift errors accumulated over time (B) It speeds up the SLAM process (C) It reduces the number of particles in the filter (D) It simplifies sensor fusion 22. Which of the following is a drawback of Visual SLAM? (A) High computational cost (B) Limited range (C) Inability to operate in the dark (D) Inability to detect colors 23. What is “Graph-based SLAM”? (A) A SLAM method that represents poses and landmarks as nodes in a graph (B) A SLAM method that uses visual graphs for mapping (C) A SLAM technique for navigating graph structures (D) A SLAM approach that optimizes the map using graph theory 24. Which sensor data fusion technique is commonly used in SLAM? (A) Linear Regression (B) Fourier Transform (C) Principal Component Analysis (D) Kalman Filter 25. In SLAM, what is “pose graph optimization”? (A) Refining the estimated poses by minimizing errors in a graph-based representation (B) Optimizing the computation of the SLAM algorithm (C) Adjusting the robot’s path based on a graph of poses (D) Mapping the environment in 3D 26. What type of SLAM is particularly effective for environments with large open spaces? (A) Visual SLAM (B) LIDAR-based SLAM (C) Acoustic SLAM (D) Thermal SLAM 27. What is “factor graph” in the context of SLAM? (A) A map of environmental factors (B) A graphical representation that models the relationships between variables (C) A tool for measuring environmental noise (D) A method for optimizing robot speed 28. What is the purpose of the “FastSLAM” algorithm? (A) To fuse multiple maps together (B) To increase the speed of SLAM algorithms (C) To efficiently solve the SLAM problem using particle filters (D) To improve the resolution of the generated map 29. Which of the following is a challenge when using GPS in SLAM? (A) Limited accuracy indoors (B) High computational cost (C) Inability to operate in daylight (D) Inability to detect small objects 30. What is a common technique for improving the robustness of SLAM in dynamic environments? (A) Increasing robot speed (B) Reducing the number of sensors (C) Using robust data association methods (D) Using a fixed map 31. Which type of environment can cause challenges for LIDAR-based SLAM? (A) Forested environments (B) Urban environments (C) Highly cluttered indoor environments (D) Featureless or uniform environments 32. What is the role of “pose estimation” in SLAM? (A) To determine the robot’s position and orientation in the environment (B) To measure the distance to obstacles (C) To detect environmental changes (D) To communicate with other robots 33. What does “Kalman filter” help with in SLAM? (A) Filtering sensor data (B) Estimating the state of a system with noise and uncertainty (C) Mapping unknown environments (D) Navigating complex paths 34. What is the purpose of “incremental SLAM”? (A) To update the map and localization incrementally as new data arrives (B) To speed up the SLAM algorithm (C) To simplify the map generation process (D) To combine multiple maps into one 35. In SLAM, what does “pose” refer to? (A) The robot’s position and orientation (B) The map’s resolution (C) The speed of the robot (D) The type of sensor used 36. Which SLAM approach is particularly well-suited for handling large-scale maps? (A) Particle Filter SLAM (B) Visual SLAM (C) LIDAR-based SLAM (D) Graph-based SLAM 37. What is the primary advantage of using “sparse mapping” in SLAM? (A) Reduced computational and memory requirements (B) Increased map detail (C) Higher accuracy in localization (D) Faster map generation 38. What does “data association” ensure in SLAM? (A) That maps are correctly merged (B) That the robot follows a specific path (C) That sensor measurements are correctly linked to map features (D) That robots can communicate effectively 39. Which technique helps in reducing the computational complexity of SLAM algorithms? (A) Particle filtering (B) Sensor fusion (C) Keyframe-based SLAM (D) Kalman filtering 40. What is “robustness” in the context of SLAM? (A) The ability of SLAM to handle errors and uncertainties effectively (B) The speed of the SLAM algorithm (C) The accuracy of the sensors used (D) The size of the map generated