Project/anca stefania.maxim (#1237)

* Added index.md file, containing short project description

Signed off: Anca-Stefania Maxim

* added block schema

* Update index.md

* Added schematic

* Added hardware pictures and logged my activity.

* Added hardware pictures and logged my activity.

Author: ancamaxim

website/versioned_docs/version-acs_cc/project/2026/anca_stefania.maxim/index.md

@@ -31,83 +31,7 @@ The system is structured in four functional layers:
 - **Mapping Layer**: 32x32 occupancy grid updated through Bresenham ray casting — builds the probabilistic obstacle map
 - **Planning Layer**: frontier-based exploration + PID on heading — decides the next destination and controls movement
 
-```mermaid
-flowchart TB
-    subgraph PERCEPTION["1. Perception layer — acquires environment and motion data"]
-        direction LR
-        US["3x HC-SR04<br/>front, left, right<br/>TIM3 input capture<br/>60 ms between reads"]
-        SERVO["SG90 servo<br/>scans front sensor<br/>5 angles: -60°..+60°<br/>PWM 50 Hz, 1-2 ms pulse"]
-        IMU["MPU-6050<br/>gyro Z + accel<br/>I2C1 at 400 kHz<br/>addr 0x68"]
-        ENC["2x Hall encoders<br/>TIM2 + TIM5<br/>quadrature mode<br/>80 counts/rev"]
-        IR["2x IR sensors<br/>edge detection<br/>ADC1 channels 11+12"]
-    end
- 
-    subgraph LOCALIZATION["2. Localization layer — estimates pose (x, y, theta)"]
-        direction LR
-        ODOM_CALC["Wheel odometry<br/>delta_s = (left + right) / 2<br/>delta_theta = (right - left) / wheelbase<br/>x += delta_s * cos(theta)<br/>y += delta_s * sin(theta)"]
-        COMP_FILTER["Complementary filter<br/>theta = 0.98 * (theta + gyro * dt)<br/>+ 0.02 * theta_odom<br/>reduces drift"]
-    end
- 
-    subgraph MAPPING["3. Mapping layer — builds 32x32 occupancy grid"]
-        direction LR
-        WORLD2GRID["World to grid<br/>cell_x = (world_x + 80) / 5<br/>cell_y = (world_y + 80) / 5<br/>5 cm per cell"]
-        BRESENHAM["Bresenham ray casting<br/>from robot to obstacle<br/>marks free cells along ray<br/>marks obstacle at endpoint"]
-        BAYES_UPDATE["Bayesian update<br/>log-odds per cell<br/>l = l + l_obs - l_prior<br/>clamp [0, 255]"]
-    end
- 
-    subgraph PLANNING["4. Planning layer — selects goal and drives motors"]
-        direction LR
-        FRONTIER_DETECT["Frontier detection<br/>find free cells adjacent<br/>to unknown cells<br/>Manhattan distance to closest"]
-        PID_CTRL["PID heading controller<br/>error = goal_theta - theta<br/>output = Kp*err + Ki*int + Kd*der<br/>anti-windup on integral"]
-        MOTOR_CMD["Motor commands<br/>L298N H-bridge<br/>PWM duty 0-100%<br/>direction via IN1-IN4"]
-    end
- 
-    subgraph OUTPUT["5. Output layer — visual feedback and PC telemetry"]
-        direction LR
-        LCD_RENDER["ST7735 LCD render<br/>SPI1 at 8 MHz<br/>128x160 px, 16-bit color<br/>grid + robot position"]
-        WIFI_TX["ESP-01 WiFi<br/>USART3 at 115200 baud<br/>RLE-compressed grid<br/>2 Hz to PC"]
-        STATUS_OUT["RGB LEDs + buzzer<br/>state indication<br/>event audio cues"]
-    end
- 
-    %% Perception flows into localization
-    ENC ==> ODOM_CALC
-    IMU ==> COMP_FILTER
-    ODOM_CALC ==> COMP_FILTER
- 
-    %% Perception flows into mapping
-    SERVO -.->|sweep angle| US
-    US ==> WORLD2GRID
-    COMP_FILTER ==>|robot pose| WORLD2GRID
-    WORLD2GRID ==> BRESENHAM
-    BRESENHAM ==> BAYES_UPDATE
- 
-    %% Mapping flows into planning
-    BAYES_UPDATE ==>|grid state| FRONTIER_DETECT
-    COMP_FILTER ==>|current pose| FRONTIER_DETECT
-    FRONTIER_DETECT ==>|target heading| PID_CTRL
-    COMP_FILTER ==>|current heading| PID_CTRL
-    PID_CTRL ==> MOTOR_CMD
- 
-    %% Output consumers
-    BAYES_UPDATE ==> LCD_RENDER
-    COMP_FILTER ==>|robot pose| LCD_RENDER
-    BAYES_UPDATE ==> WIFI_TX
-    IR ==> STATUS_OUT
-    FRONTIER_DETECT ==>|exploration done?| STATUS_OUT
- 
-    classDef perceptionStyle fill:#E6F1FB,stroke:#185FA5,stroke-width:1px,color:#042C53
-    classDef localizationStyle fill:#FBEAF0,stroke:#993556,stroke-width:1px,color:#4B1528
-    classDef mappingStyle fill:#FAECE7,stroke:#993C1D,stroke-width:1px,color:#4A1B0C
-    classDef planningStyle fill:#FAEEDA,stroke:#854F0B,stroke-width:1px,color:#412402
-    classDef outputStyle fill:#EAF3DE,stroke:#3B6D11,stroke-width:1px,color:#173404
- 
-    class US,SERVO,IMU,ENC,IR perceptionStyle
-    class ODOM_CALC,COMP_FILTER localizationStyle
-    class WORLD2GRID,BRESENHAM,BAYES_UPDATE mappingStyle
-    class FRONTIER_DETECT,PID_CTRL,MOTOR_CMD planningStyle
-    class LCD_RENDER,WIFI_TX,STATUS_OUT outputStyle
-```
-
+![Block Scheme](schema_bloc.svg)
 
 ### Processing Pipeline
 
@@ -129,17 +53,23 @@ At each 100ms cycle, the system executes sequentially:
 
 ### Week 5 - 11 May
 
+Decided upon hardware components and designed a block scheme with the hardware architecture I will built.
+
 ### Week 12 - 18 May
 
+Asembled hardware components, tested each component (to verify its functionality) through simple tasks and finalized hardware implementation.
+
 ### Week 19 - 25 May
 
 ## Hardware
 
 The robot is built on a 2WD chassis with two DC motors with Hall encoders for precise odometry. Three HC-SR04 ultrasonic sensors (front, left, right) mounted on an SG90 scanning servo provide obstacle detection. An MPU-6050 IMU handles heading correction, while two IR sensors detect floor edges. An ST7735 128x160 color LCD displays the live map, and an ESP8266 WiFi module streams data wirelessly to a PC. The system is powered by a 7.4V 2000mAh LiPo battery with an LM2596 voltage regulator.
 
+![Hardware](masina_slam.webp)
+
 ### Schematics
 
-Place your KiCAD or similar schematics here in SVG format.
+![Project Schematic](project_schematic.svg)
 
 ### Bill of Materials