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Name: LFE2-12E-5QN208C
Brand: Lattice Semiconductor Corporation
SKU: LFE2-12E-5QN208C
Price: 2.40 USD
Availability: InStock
Rating: 5 (2 reviews)

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Lattice Semiconductor Corporation LFE2-12E-5QN208C

Part No.:: LFE2-12E-5QN208C

Manufacturer:: Lattice Semiconductor Corporation

Package:: 208-BFQFP

Datasheet:: LFE2-12E-5QN208C.pdf

Description:: IC FPGA 131 I/O 208QFP

In Stock:: 2991

Quantity:: Add To Cart

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LFE2-12E-5QN208C Specifications

Package/Case:
208-BFQFP
Packaging:
Tray
Series:
ECP2
ProductStatus:
Active
NumberofLABs/CLBs:
1500
NumberofLogicElements/Cells:
12000
TotalRAMBits:
226304
NumberofI/O:
131
NumberofGates:
-
Voltage-Supply:
1.14V ~ 1.26V
MountingType:
Surface Mount
OperatingTemperature:
0°C ~ 85°C (TJ)

LFE2-12E-5QN208C this integrated circuit is available in factory sealed anti static packs. at icwhale.com. Please read product page below detail information. including LFE2-12E-5QN208C price, data-sheet, in-stock availability, technical difficulties. Also. Quickly Enter the access of compare listing to find out replaceable electronic parts. If you want to retrieve comprehensive data for LFE2-12E-5QN208C to optimize the supply chain (including cross references, life-cycle, parametric, counterfeit risk, obsolescence managements forecasts), please contact to our Tech-supports team.

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LFE2-12E-5QN208C information

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LFE2-12E-5QN208C application case analysis in emerging technology fields

LFE2-12E-5QN208C is a field-programmable gate array (FPGA) device known for its high efficiency and versatility in embedded systems applications. It features low power consumption, ample logic resources, and advanced programmable features.

Application Scenario:

In autonomous robotics, LFE2-12E-5QN208C can revolutionize navigation systems by enabling real-time decision-making and adaptive path planning.

System Architecture:

To implement autonomous navigation using LFE2-12E-5QN208C, the following architecture can be employed:

1. Sensor Integration:

Integrate various sensors such as LiDAR, cameras, and inertial measurement units (IMUs) to capture environmental data. Interface these sensors with LFE2-12E-5QN208C through its GPIO pins, such as pin N1 and pin M1.

2. Data Processing:

Use the programmable logic resources of LFE2-12E-5QN208C to preprocess sensor data in real-time. Implement algorithms for obstacle detection, localization, and mapping (SLAM) to create a comprehensive understanding of the robot's surroundings.

3. Path Planning:

Utilize the FPGA's computational capabilities to perform complex path planning algorithms, considering dynamic obstacles and environmental constraints. Implement algorithms such as A* or RRT* to generate optimal trajectories.

4. Control System:

Develop control algorithms to navigate the robot along the planned path while ensuring collision avoidance and smooth motion. Use LFE2-12E-5QN208C's flexible IOs, such as pin C1 and pin D1, to interface with motor controllers and actuators.

5. Communication:

Implement communication protocols like CAN or Ethernet to facilitate coordination between multiple robots or interaction with a central control station. Configure the FPGA's serial transceivers, such as pin A1 and pin B1, for reliable data exchange.

Benefits:

Using LFE2-12E-5QN208C in autonomous navigation systems offers several advantages:

- Real-time Adaptability: The FPGA's reconfigurability allows for on-the-fly adjustments to navigation algorithms based on changing environmental conditions.

- High Performance: The parallel processing capability of the FPGA enables rapid data processing and decision-making, crucial for safe and efficient navigation.

- Low Power Consumption: LFE2-12E-5QN208C optimizes energy usage, extending battery life in mobile robotic platforms and reducing overall operational costs.

- Customization: Developers can tailor navigation algorithms and control strategies to specific application requirements, maximizing system effectiveness.

Considerations:

- Resource Utilization: Efficient utilization of FPGA resources is essential to accommodate all necessary functionalities without exceeding hardware limitations.

- Sensor Fusion: Proper integration and synchronization of sensor data are critical for accurate perception and decision-making.

- Safety: Robust fail-safe mechanisms should be implemented to ensure the safety of the robot and its surroundings in case of hardware or software failures.

- Testing and Validation: Thorough testing and validation procedures are necessary to verify the reliability and performance of the autonomous navigation system in diverse operating scenarios.

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6. What is the process for return or replacement of LFE2-12E-5QN208C?

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(1)Such as a deficiency in quantity, delivery of wrong items, and apparent external defects (breakage and rust, etc.), and we acknowledge such problems.

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