Unlocking robot motion

SUPERPOWER

Developer of general-purpose robot "cerebellum"

Covering bipedal and quadrupedal robot motion control,

perception, and planning

Contact Now

The best choice of general robot motion control

The Best in General Robotics Motion Control

Empowering humanoid robots to achieve human-like movements based on high-precision motion capture data and reinforcement learning algorithms

Empowered by high-precision motion capture data and reinforcement learning algorithms, BridgeDP enables humanoid robots to perform human-like actions.

Humanoid robot dance

Exclusively realized AGIBOT A2 robot

Booster of T1 robotics

Achieve humanoid robot dancing

Watch Video

Humanoid robot dance

Exclusively realized AGIBOT A2 robot

Booster of T1 robotics

Achieve humanoid robot dancing

Watch Video

Humanoid robot dance

Exclusively realized AGIBOT A2 robot

Booster of T1 robotics

Achieve humanoid robot dancing

Watch Video

Bridge the gap of Sim2Real

Based on reinforcement learning, phased and multi-level reward mechanisms

Enables the agent to gradually adapt to the real environment

Based on reinforcement learning, a phased, multi-level reward mechanism can enable agents to gradually adapt to real-world environments.

Robot dog with perception for climbing up and down stairs

Already implemented by Unitree Robotics GO1

Robot dog, perceives ascending and descending stairs

Watch Video

Solution

Bipedal robot motion control algorithm

High versatility and multi-hardware adaptability, performance reaching world-leading levels

Watch video

Watch Video

Watch video

Cutting-edge algorithms

Policy optimization algorithm based on deep reinforcement learning

Fusion Algorithm

Based on Learning-based Algorithm

Motion Capability

Anthropomorphic walking (straight knee walking) interaction (dancing, greeting, etc.)

Rapid compatibility

Quickly adapt to various custom bipedal and quadrupedal robot hardware

Quickly adapt to various custom bipedal and quadrupedal robotic hardware.

High versatility and multi-hardware adaptability, performance reaching world-leading levels

Watch video

Watch Video

Cutting-edge algorithms

Policy optimization algorithm based on deep reinforcement learning

Fusion Algorithm

Based on Learning-based Algorithm

Motion Capability

Anthropomorphic walking (straight knee walking) interaction (dancing, greeting, etc.)

Rapid compatibility

Quickly adapt to various custom bipedal and quadrupedal robot hardware

Quickly adapt to various custom bipedal and quadrupedal robotic hardware.

Perception Solution
for Going Upstairs and Downstairs

Integrating Multimodal Perception and Real-time Decision-making to Achieve Accurate Recognition and Safe Passage for Robots on Stairs and Complex Terrain

Watch video

Watch Video

Multimodal Fusion Perception

Environment perception based on vision and radar

Perception + Planning

Integrating perception and planning to achieve intelligent passage.

Perception + Planning

Integrating perception and planning to achieve intelligent passage.

High Dynamic Motion Capability

Quadruped switching to biped + small dinosaur upright gait

High Dynamic Motion Capability

Quadruped to Biped Switch + Little Dinosaur Upright Gait

Mobile Operations

Combined operation of foot chassis and robotic arm

Mobile Operations

Combined operation of the foot-type chassis and robotic arms

Specifically designed

for bipedal and quadrupedal robots

Provide motion control solutions

50+

As of Q1 2025

BridgeDP solutions have been deployed to 20+ robot manufacturers

Covering humanoid, quadruped, and wheeled-legged models, etc

41%

2024 World Robot Conference (WRC)

Among the 27 participating robot manufacturers, 11 have been served

39%

2024 World Artificial Intelligence Conference (WAIC)

Among the 18 exhibiting robot manufacturers, 7 have been served

Specifically designed

for bipedal and quadrupedal robots

Provide motion control solutions

50+

As of Q1 2025

BridgeDP solutions have been deployed to 20+ robot manufacturers

Covering humanoid, quadruped, and wheeled-legged models, etc

41%

2024 World Robot Conference (WRC)

Among the 27 participating robot manufacturers, 11 have been served

39%

2024 World Artificial Intelligence Conference (WAIC)

Among the 18 exhibiting robot manufacturers, 7 have been served

Core Delivery

Efficient delivery, comprehensive coverage, the strongest legged motion control solution

Based on modular motion control and iterative learning algorithms,

to assist customers in efficiently adapting to various robotic forms and application scenarios

High cost performance

Provides "motion control algorithms" based on the hardware itself to support customers in calling basic motion modules on demand

Development cost reduction

60%

Rapid Delivery

Traditional R&D cycles often require 3 to 4 months, but we can significantly reduce this to a few weeks

Improvement in development efficiency

3~4 times

High market share

Covers humanoid robots, quadrupedal robot dogs, and wheeled-legged hybrid models

Bridge solution deployment exceeds

20+

Ultra-fast iteration

Based on learning-based algorithms, continuously developing new action sets

Algorithm Upgrade

Monthly Iteration

High cost performance

Provides "motion control algorithms" based on the hardware itself to support customers in calling basic motion modules on demand

Development cost reduction

60%

Rapid Delivery

Traditional R&D cycles often require 3 to 4 months, but we can significantly reduce this to a few weeks

Improvement in development efficiency

3~4 times

High market share

Covers humanoid robots, quadrupedal robot dogs, and wheeled-legged hybrid models

Bridge solution deployment exceeds

20+

Ultra-fast iteration

Based on learning-based algorithms, continuously developing new action sets

Algorithm Upgrade

Monthly Iteration

High cost performance

Provides "motion control algorithms" based on the hardware itself to support customers in calling basic motion modules on demand

Development cost reduction

60%

Rapid Delivery

Traditional R&D cycles often require 3 to 4 months, but we can significantly reduce this to a few weeks

Improvement in development efficiency

3~4 times

High market share

Covers humanoid robots, quadrupedal robot dogs, and wheeled-legged hybrid models

Bridge solution deployment exceeds

20+

Ultra-fast iteration

Based on learning-based algorithms, continuously developing new action sets

Algorithm Upgrade

Monthly Iteration

About Us

General robot motion control developer

BridgeDP is an industry-leading developer of general robot "cerebellum," covering bipedal and quadrupedal robot motion control, perception, planning, and other fields

BridgeDP is committed to breaking through the efficiency bottlenecks and physical transfer challenges of traditional robot motion development, helping customers quickly realize complex motion functions of quadrupedal robots (such as precise walking, high-speed running, dynamic jumping, multi-terrain adaptation, and high-precision dance movements) while providing underlying technical support for core scenarios such as balance control and full-body coordination of bipedal humanoid robots.

Investor

News Information

桥介数物再获新融资：深创投独家投资

加速桥介平台化全球化战略布局

桥介数物亮相2025机器人大会

三大核心技术筑牢通用机器人“小脑”基石

桥介数物完成近亿元融资

通用机器人感控一体动作开发平台

Contact Us

Contact Number

+86 185 7553 5266

WeChat

bridgedp

Official WeChat

Latest updates and more

Github

Humanoid Robot
Open Source Control Scheme

BridgeDP BridgeDP

Robotic Demo Video

Unlocking robot motion

SUPERPOWER

Developer of general-purpose robot "cerebellum"

Covering bipedal and quadrupedal robot motion control,

perception, and planning

The best choice of general robot motion control

The Best in General Robotics Motion Control

Empowering humanoid robots to achieve human-like movements based on high-precision motion capture data and reinforcement learning algorithms

Empowered by high-precision motion capture data and reinforcement learning algorithms, BridgeDP enables humanoid robots to perform human-like actions.

Humanoid robot dance

Humanoid robot dance

Humanoid robot dance

Bridge the gap of Sim2Real

Based on reinforcement learning, phased and multi-level reward mechanisms

Enables the agent to gradually adapt to the real environment

Based on reinforcement learning, a phased, multi-level reward mechanism can enable agents to gradually adapt to real-world environments.

Robot dog with perception for climbing up and down stairs

Solution

Bipedal robot motion control algorithm

High versatility and multi-hardware adaptability, performance reaching world-leading levels

High versatility and multi-hardware adaptability, performance reaching world-leading levels

Perception Solution for Going Upstairs and Downstairs

Integrating Multimodal Perception and Real-time Decision-making to Achieve Accurate Recognition and Safe Passage for Robots on Stairs and Complex Terrain

Specifically designed

for bipedal and quadrupedal robots

Provide motion control solutions

50+

50+

Specifically designed

for bipedal and quadrupedal robots

Provide motion control solutions

50+

Core Delivery

Efficient delivery, comprehensive coverage, the strongest legged motion control solution

Efficient delivery, comprehensive coverage, the strongest legged motion control solution

Based on modular motion control and iterative learning algorithms,

to assist customers in efficiently adapting to various robotic forms and application scenarios

About Us

General robot motion control developer

BridgeDP is an industry-leading developer of general robot "cerebellum," covering bipedal and quadrupedal robot motion control, perception, planning, and other fields

Investor

News Information

桥介数物再获新融资：深创投独家投资

桥介数物亮相2025机器人大会

桥介数物完成近亿元融资

Contact Us

Perception Solution
for Going Upstairs and Downstairs