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Axibo Research
Quadruped robot design
& navigation
- Quadruped for mapping & Surveillance
- Navigation remotely or through lidar autonomous P2P stack
- Build cost < $2K (excluding sensory suite)
Introduction
For more than 50 years scientists and engineers have been experimenting with walking machines inspired by biomimicry such as legged robots that balance and other examples such as DASH: A resilient high-speed 15g hexapedal robot. A lot of recent research activities have been inspired by Boston Dynamics work on BigDog, the Rough-Terrain Quadruped Robot.
At AXIBO, we are exploring on prototyping and streamline the production of these robots for different applications. In addition we are exploring how different materials can be used for constructing different parts of these robots for specific applications. Focused on improving the main components such as the body material, battery pack, sensor feedback, and control system.
At AXIBO, we are exploring on prototyping and streamline the production of these robots for different applications. In addition we are exploring how different materials can be used for constructing different parts of these robots for specific applications. Focused on improving the main components such as the body material, battery pack, sensor feedback, and control system.
Contents
Main objective was to design the base robotic dog model that is built cost effectively and to accomplish the same tasks that a high-end expensive models would be expected to deliver.
Main components that were created are as follows: Battery pack, Sensor feedback, Control system, and Body design. These improvements were made while keeping ease of manufacturing and cost of production in mind.
For rapid prototyping purposes, FormLabs 3BL SLA (Stereolithography) 3D printer was used for printing most of the body parts and the Tough 1500 resin material was used. This specific resin allowed strong structural rigidity as well as the flexibility needed for the robotic dogs main components. Improvements on the physical structure allowed different mounting systems to mount cameras, Lidars, and robotic arms.
Unlock the opportunities
These attachments allowed more applications for the Robot. Further improving its use cases and applications while keeping costs low.
Visual and Lidar based Simultaneous Localization and Mapping (SLAM) can now be implemented on this robot platform.
Allowing possibility for the robot to autonomously roam and set directions. Autonomous drivability is crucial in automated data collection to increase efficiency and safety. With sensory feedback system, robots course of actions can be automated while accounting for non planned obstacles such as changes in its environment. It can avoid obstacles such as people, machinery, and environmental weather conditions. Autonomous drive ability allows it to be well suited for work environments that could be dangerous for human workers or even for recon missions. Opening up the field of opportunities in national defense.
Conclusion
To conclude, research and development of the robotic dog platform allowed further expansions in its use cases in real life scenarios. Enhancements in software as well as mechanical properties expanded it's ability to be used autonomously. Expanding its applications for surveillance and data collection purposes. We hope to further expand and test its capability in the filed of national defense as well as urban work areas.
Looking for efficient and cost-effective way to automate your operations?
Axibo Research
Infrastructure-based
Autonomous System
Description
The goal of this project was to create a new form of the autonomous system - one where the sensors are not on the robots, but mounted on various forms of infrastructure such as buildings and street poles.
Edge computing hardware collects data from a LiDAR sensor, which is later merged with various LiDARs across a variety of edge nodes, giving us a high-quality map of an entire city or region. From here, we can locate robots and vehicles we want to control, and begin giving commands based on various path-planning algorithms.
Progress Recording: https://drive.google.com/file/d/1RjL3Y3koFQoi1-wB3CBv734iHj2BbQk1/view
Technologies
LiDAR, obstacle avoidance, PLC, path planning, 3D mapping. (Everything designed from scratch, custom PCB/electronics, custom panels, custom motors, custom compute unit.)
Looking for efficient and cost-effective way to automate your operations?
Axibo Research
An autonomous golf cart
(Capstone project)
Description
- Designed & implemented drive by wire system (PCB, Motor controls, networking)
- Developed object detection stack (deep learning)
- Developed and implemented navigation and path planning stack (ROS, Lidar, Camera)
- Power electronics for solar power/charging
Looking for efficient and cost-effective way to automate your operations?
Axibo Research
Robotic Charging
System
Description
In this initial prototype version, the three main components of the robotic arm consist of an actuator (for gripping the charger), a single-point LiDAR (for pose correction), and a camera (for computer vision).
What you'll see in the video is the robot switching from its camera frame to its SP LiDAR frame. In essence, computer vision for localization, and LiDAR for fine-tuning corrections.
Looking for efficient and cost-effective way to automate your operations?
Axibo Research
Learning Factory Laboratory
(Contract for McMaster University)
Description
Design and build an ‘industry 4.0’ lab at McMaster university. The idea was to create a totally end-end mini factory, using autonomous moving robots and collaborative arms.
Our tasks included building out hardware (robots, workstations, automation rigs) and the software infrastructure to connect all things together.
Industry 4.0 Experience: https://www.eng.mcmaster.ca/sept/practice/learning-factory/
Technologies
IoT, CNC automation, Automatic motor winding, AVG, Collaborative robots
Looking for efficient and cost-effective way to automate your operations?
Axibo Research
Autonomous AGV
for part delivery
Description
An autonomous ground vehicle, designed from the ground up with integrated sensors and computing capabilities.
Users are able to control the robot remotely, or provide it goals on where to go, i.e. on a map where the robot should end off. Using various 2D and 3D sensors, the robot will localize itself on a map, create a path to its goal, and avoid obstacles on the way there. “The global autonomous mobile robots market size was valued at USD 1.9 billion in 2019 and is expected to grow at a compound annual growth rate (CAGR)of 19.6% from 2020 to 2027.
Technologies
LiDAR, Obstacle avoidance, PLC, Path planning, 3D mapping (Everything designed from scratch, Custom PCB/electronics, Custom panels, Custom motors, Custom compute unit.)
