Robot Car with LiDAR

Robot Car with LiDAR is a project to build a robot car with a LiDAR sensor to navigate the environment and avoid obstacles. The car uses a tank track with 4 DC motors. It can be controlled by a remote control or can be driven autonomously.

There are 3 operational modes: Manual, Autonomous, and Semi-Auto.

• Manual mode is controlled by a remote control (LiDAR disabled).
• Autonomous mode is controlled by the LiDAR sensor with smart navigation.
• Semi-Auto mode is a combination of the Manual and Autonomous modes, it can avoid obstacles even when it is controlled by the RC.

Smart Navigation System

The autonomous mode uses a Vector Field Histogram (VFH) inspired algorithm for intelligent obstacle avoidance. Instead of simple reactive turns, the robot builds a spatial model of its surroundings and selects the probabilistically best path.

How It Works

1. Sector-Based Mapping - The 180° front field-of-view is divided into 12 sectors (15° each). Each LiDAR point is accumulated into its corresponding sector, building an obstacle density histogram per full scan.

2. Weighted Density Scoring - Closer obstacles contribute exponentially more to a sector's density using inverse-square weighting (1/d²). This makes the robot more sensitive to nearby threats while still accounting for distant objects.

3. Multi-Factor Path Selection - Each sector is scored by combining:

   • Openness (primary) - sectors with less obstacle density score higher.
   • Distance - prefers paths where the nearest obstacle is further away.
   • Gap Width - favors wider openings by checking adjacent sectors.
   • Center Preference - slight bonus for going straight to avoid unnecessary deviation.
   • Heading Continuity - prefers directions close to the current heading for smoother motion.

4. Proportional Steering - Instead of binary hard-left/hard-right turns, steering is proportional to how far the best path is from the current heading, producing smooth, natural turns.

5. Temporal Smoothing - An exponential moving average blends current and previous scans (alpha = 0.3) to filter out noise and prevent erratic oscillation.

6. Graduated Speed Control - The robot slows down proportionally as it approaches obstacles:

   • Full speed when clear (> 35cm).
   • Linear deceleration from 35cm down to 16cm.
   • Emergency stop and smart reverse at 16cm or closer.

Tunable Parameters

Parameter	Default	Description
NUM_SECTORS	12	Number of angular sectors (higher = finer resolution)
SMOOTHING_ALPHA	0.3	Temporal smoothing factor (lower = smoother, slower reaction)
MAX_LIDAR_DISTANCE_CM	50	Maximum detection range in cm
SLOW_DOWN_DISTANCE_CM	35	Distance at which the robot begins to decelerate
MIN_SAFE_DISTANCE_CM	16	Emergency stop distance threshold

Hardware

Components

• Arduino Mega 2560 REV3 (https://amzn.to/3wObNdW)
• Slamtec RPLIDAR A1M8 (https://amzn.to/3VaSoy3)
• 7.4V 1200mAh Lipo Battery (https://amzn.to/3Pdja4Z)
• L298N Motor Driver Controller Board (https://amzn.to/3TxBqc0)
• FLYSKY FS-i6X 10CH 2.4GHz RC Transmitter (https://amzn.to/3wP557x)

Pin Configuration

Motors (via L298N)

Pin	Function
2	Left Motor Direction 1
3	Left Motor Direction 2
4	Right Motor Direction 1
5	Right Motor Direction 2
6	Left Motor Speed (PWM)
7	Right Motor Speed (PWM)

RP LiDAR Motor

Wire	Function
Purple	PWM control (Pin 8)
Yellow	Motor GND
Red	Motor +5V

The LiDAR motor runs at 9V. The PWM wire is connected to Arduino Mega Pin 8 to control motor speed.

RP LiDAR Sensor (Serial1)

Wire	Function
White	Ground
Black	5V
Orange	RX
Green	TX

RC Receiver (IBus protocol on Serial2)

Channel	Function
CH1	Left / Right steering
CH2	Forward / Reverse
CH3	Throttle
CH4	Rudder (unused)
CH5 (AUX1)	Mode selector (< 10 = Manual, > 10 = Autonomous)