* **Reading: <a href="/content/topics/homeworks/hw_readings_119/190_hw_119_prr10_1/">Read PRR Chapter 10</a>** * **Reading: <a href="/content/topics/homeworks/hw_readings_119/200_hw_119_prr10_2/">Read PRR Chapter 10 Part 2</a>** *Reminder: Readings are your responsibility. You will be expected to come to class prepared, having read the material, and ready to participate in the discussion* <slide_break></slide_break> ## Logistics <slide_break></slide_break> ### Next class: QUIZ! * In class, no web, no book * No coding nor memorizing of APIs * It will be technical * If you have attended (to) class, did the readings, and completed the PAs * You should have no trouble <slide_break></slide_break> ### Student Lab Manangers * Can't decide on term, used to be Deputy TA * Currently: * Vendashi: vedanshi@brandeis.edu * Artem: artemlavrov@brandeis.edu * Sam: samuelherman@brandeis.edu * Looking for a few more! * If you want to be considered as a Student Lab Manager, send me an email <slide_break></slide_break> ### Expectations for the Term Project * You will be using the lab outside of formal lab times * Coordinate with the TAs and Student Lab Managers * Starting now the majority of your “homework” will be your term project. * Expect 5-10 hours a week per student * This is work outside the classroom (and also outside lab time) * You will need to plan and manage your time to achieve this <slide_break></slide_break> ## Review of Slam * **[Great Resource](https://github.com/AtsushiSakai/PythonRobotics?tab=readme-ov-file)** 1. An algorithm that builds up a map while collecting sensor and analyzing it statistically 2. The map as it is being built is published by the map_server 3. You can save the map to a file so that it remembers it to the next run 4. Map Consists of a grid of "costs" (costmap) and a coordinate system 2. Map server "publishes" the map on the /map topic 3. Costmaps are actually multi-layered <slide_break></slide_break> ### Navigation 1. AMCL: Given lidar sensor data and a map, estimates the true location of the robot 2. Calculation is reset when amcl receives a new pose_estimate 3. This estimate is different from /odom (why?) 4. AMCL publishes a /tf transform between /map and /odom (note this is the "highest probability" location) <slide_break></slide_break> ### ROS Actions * Built on top of ROS Topics * Used for the key navigation service, `move_base` * Actions implement a protocol where a node (requestor) can request a long-running action from another node (actor) * Compare with topic publishing which are one-shot * Requestor: * Does not need to know anything about how to actor works * Can ask to initiate an action (e.g. navigate to x,y) * Can find out the progress or status of the action (which can take many seconds) * Is notified when the action is finished, either successfully or unsuccessfully * Actor: * Receives the request from the requestor * Proceeds to implement the action * REports status as requested * Reports completion, either successful or failure * Book: <a href="/content/topics/robotics/ros_book/50_prr_actions/">5: Actions</a> <slide_break></slide_break> ### ROS Services * Built on top of ROS topics * Used as a way to allow a node to receive requests (synchronously) and return a response * Also used as part of move_base. <slide_break></slide_break> ## move_base - The big enchilada of ROS Navigation * Main entry point of ROS navigation algorithms * Conceptually: move_base(x,y) - causes the robot to do it's best to get to x,y * But there must be a lot more to it. <div class="discussionbox"><strong>Discussion:</strong> what else must be involved?</div> * A large diverse collection of packages and modules * A sophisticated, pluggable architecture * Allows for new algorithms to be designed and tested * Parameterized for configuration * Uses ROS "actions" to initiate, monitor, and report success * Initial goal is: /MoveBaseActionGoal <slide_break></slide_break> ### Components of move_base * Global Planner: Creates a plan from the current position (AMCL) to the goal position with respect to a map. May use any of a number of algorithms (including A*) * Local Planner: Given the local map (built in real time from sensors), considers location and velocity and computes the near part of the plan. * costmap-2d: General package to build, maintain, update and access a multi-layer 2d map. Used for both local and global maps and for other things * Recovery behaviors: either map clearing or rotation recovery heuristics used when robot appears to be stuck. <slide_break></slide_break> ### FLows <img src="/content/topics/images/move_base.jpg" class="img-thumbnail d-block mx-auto" style="height:300px;"/> <slide_break></slide_break> ### How move_base works - global planner 1. Uses base_global planner to comnpute a path from current position to goal 2. This plan is with respect to the global costmap (from /map topic and `map_server`) 3. Look at [ROS global planner](http://wiki.ros.org/global_planner) for visuals 4. Interesting parameters: <pre><code class="language-bash"> /use_dijkstra (bool, default: true) # If true, use dijkstra's algorithm. Otherwise, A*. /use_quadratic (bool, default: true) # If true, use the quadratic approximation of the potential. Otherwise, use a simpler calculation. /use_grid_path (bool, default: false) # If true, create a path that follows the grid boundaries. Otherwise, use a gradient descent method. </code></pre> <slide_break></slide_break> ### How move_base works - local planner 1. Create a local map grid from the local costmap) with costs representing distances to the final goal 1. Uses base_local_planner to determine the next motion in the immediate future <slide_break></slide_break> ### The two book chapters * <a href="/content/topics/robotics/ros_book/110_prr_navigating/">10 part2: Navigating</a> * <a href="/content/topics/robotics/ros_book/115_prr_move_base/">10 part3: Move Base</a> <slide_break></slide_break> ### Topics for further study * The [SLAM Toolbox](https://docs.google.com/presentation/d/1S9aWpgOkojcgA691gmt-359m9RtjTR2Yhm9Zmjh5Yjg/edit) * The [Python Robotics Pacakge](https://github.com/AtsushiSakai/PythonRobotics#documentation) <slide_break></slide_break> <h2 class="shadow p-3 bg-white rounded">Thank you. Questions?<img class="img-fluid w-100" src="https://picsum.photos/800/100.jpg" /> <small> (random Image from picsum.photos)</small></h2>