Our CTO (Luke Cole) previously worked for Hemisphere GPS (orginally called BEELINE, and now bought out by AgJunction) as a "Robotics Engineer" implementing auto-guidance solutions for various quadbikes and agriculture tractors that was used by 100's of vehicles around the world.

For 10 years, starting as a teenager in 1998 - Luke Cole has also worked for leading research institutes and companies such as NICTA (now called CSIRO Data61), CSIRO, Seeing Machines and ANU Robotics System Lab (lead by Alex Zelinsky, who received a rare prestigious AO award in 2017 and was Defence Scientist of Australia from 2012 for 6 years). Luke's worked included various autonomous mobile robot projects, involving computer vision, and even a self-driving car early 2000's. Back then OpenCV and ROS didn't exist, so we did a "roll-your-own" called VisLib and DROS comprised of 364,578 lines of code.

Lance Cole has also worked at NICTA and has a background of various hardware development, such as working for a contract company to the US millary (EOS), building the Common Remotely Operated Weapon Station (CROWS).

We have a long-standing robotics experience - our engineers offering Robotics Prototyping for Gungalman, robot development and robotics custom software services have something like a combined 50 years worth of experience in the robotics field, from teleoperated and semi-autonomous mobile robotic applications, to custom software and/or custom hardware for general automation solutions, signal processing and control systems. Our knowledge base started in NSW and ACT, but now we primarily service East Coast Queensland.

We have developed autonomous mobile robots for air, underwater and ground. Our professional experience started with developing various control and sensor systems for small underwater vehicles in the late 1990's. We where fortunate enough to have been involved in one of the first self-driving car R&D projects back in early 2000's using a 4WD (to support computers for the large processing requirements). For an overseas client we developed a low profile (70mm high) semi-autonomous mobile robot platform for manikin/dummy mounting to simulate people moving (for vehicle crash safety and collision development by German R&D car manufactures). We have been fortunate enough to have been invited to the bulk of the German R&D car manufactures where they develop and test self-driving and driver assist development systems. We have developed various solutions for 2cm accuracy precision steering-guidance solutions for various types of Agriculture tractors (via the CAN bus and ad-hoc methods), which are still used by 1000's of tractors all over the world. We have retro fitted Quadbikes to allow semi-autonomous control via GPS way points. We have custom developed various indoor mobile robotics for indoor localistion and SLAM R&D purposes.

Robot navigation is the task where an autonomous robot moves safely from one location to another. This involves three primary questions:

  1. “Where am I?” which is known as robotic localisation (hard).
  2. “Where am I going?” which is known as goal recognition (typically provided by a human).
  3. “How do I get there without collisions?” - path planning (easy) and obstacle avoidance (hard).

For robotic localisation and obstacle avoidance we use sensors to solve the problem. To move along the planned path, we use control systems.

We have a deep understanding of signal processing and sensors of various types. We appreciate sensing is a hard problem. There is no one-size-fits all solution. Odemetry (wheel encoders) provide a cost-effective method to measure relative position. however suffer from wheel slip and errors are accumlate over time. GPS only works outdoors, effected by trees/buildings, and without a nearby basestation (for expensive DGPS/RTK) the absolute position error is several meters. IMU (accelerometers + gyros + Magnetometer) suffer from drift errors and noise error causing ``random walk'' when integrated. Magnetometer are effected by magnets, are slow to respond and measure magnetic north (not true north). Infrared are cost-effective, but short range and saturated by sunlight. Ultrasonic range sensors are cost-effective and good for detecting large objects, but can't detect glass/water, only measure a few metres, have a wide beam and provide medium accuracy. RADAR uses radio (instead of sound) to detect objects at long distance, but are relative more expensive then ultrasonic range sensors. Image sensors (video cameras) are a cost-effective, rich in information, and two or more can get depth information, but are computationally expensive, hard to process the data (aka computer vision), affected by dust/fog/rain, and light variations. LIDAR are high accuracy (about 1mm), however are expensive (prices are coming down every year), but can't detect glass/water. Distance measurement sensors are easy to interpret, other sensors are hard. Colour constancy and object classification is very hard (e.g. “Is it a tree or a human?”).

We have a deep understanding of control systems. We typically use Linux-based SBC's and a program a custom PID controller - perhaps even a cascade PID controller, bayesian filters, particle filters, kalman filters, Monte Carlo methods, or train a deep neutral network. The outputs of these systems might control various types of motors (e.g. brushed, brushless, servo, steppers) and/or various types of actuators (e.g. linear, pneumatic, hydraulic), and/or other things like lights or speakers.

We have been involved with computer vision and machine vision since early 2000's - we where involved in the development of two computer vision libraries before OpenCV became popular. Have done much biologically inspired techniques such as optical flow. Was involved in the early days of artificial intelligence using techniques such as Local Binary Patterns (LBP) and Haar-like features (HAAR). These days we typically use machine learning methods such as designing and training deep neural networks (outstanding for vision-based object recognition using ImageNet).

We where involved in the development of a robotic operating system which had 364,578 lines of code, before ROS was written.

We have developed custom software for various manipulators, and have a good understanding of forward and inverse kinematics.

We appreciate that challenges with robotics - particularly with robot navigation, computer/machine vision, and manipulation with the real-world, in real-time using real-robots.

Whilw we can custom develop robot navigation solutions. We can fast-track robot navigation solutions for ground, air and water based platforms via off-the-shelf autopilots. There are many about these days. Some cost-effective open-source options include Pixhawk 4, PX4, and ArduPilot. Some expensive closed-source options include Auterion Skynode, Tersus AutoSteer, Embention Veronte, Outback eDriveX and Trimble EZ Pilot.

We are confident with a broad range of skills and confident our Robotics Prototyping for Gungalman services can offer solutions such as:

These technologies can be used for various applications such as:

We also offer a R&D robotic platform UGV for hire to help rapid development of robotics systems. If you'd like to know more please visit "Scotty Robot".

Some of our Robotics Prototyping for Gungalman and Custom Development Experience

Information About Gungalman

Strengthening the Central West Slopes: COLETEK's Commitment to Gungalman Businesses

In the heart of New South Wales' picturesque Central West Slopes, Gungalman is a thriving hub of local enterprises and community spirit. As a trusted Australian company, COLETEK recognizes the importance of fostering strong connections with businesses in this rich region. We're dedicated to supporting the growth and development of companies like yours, providing expert guidance and innovative solutions tailored to your unique needs.

Nestled among the rolling hills and expansive farmland, Gungalman's small-town charm is matched only by its resilience and entrepreneurial drive. As local businesses continue to thrive, COLETEK remains committed to being an integral part of this community. Our team understands the challenges faced in the region, from unpredictable weather patterns to supply chain disruptions. With our nation-wide reach and extensive expertise, we're well-equipped to help businesses like yours adapt, innovate, and flourish.

At COLETEK, we pride ourselves on being a locally grounded Australian company with a national footprint. Our presence gives us a unique understanding of the Gungalman community's needs, allowing us to deliver targeted support that meets your specific requirements. Our team is composed of industry experts who have worked extensively in rural and regional areas like the Central West Slopes, ensuring you receive tailored guidance and advice.

We believe that building strong relationships with local businesses is key to long-term success. As a trusted partner, COLETEK invests time and resources in getting to know your operations, goals, and challenges. Our passion for innovation stems from recognizing the importance of embracing new technologies, best practices, and creative solutions to overcome the unique hurdles faced by Gungalman businesses.

If you're looking for a trusted ally to help your business thrive in Gungalman, look no further than COLETEK. We invite you to explore our extensive range of solutions, built upon national expertise and local knowledge. As the Central West Slopes continue to grow and evolve, we stand ready to support your journey every step of the way.

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Robotics Prototyping for Gungalman – Our Clients: Big Brands & Small Businesses


Robotics Prototyping for Gungalman – Amazing Customer Testimonials

Intuitive, innovative & efficient are three words that would appropriately describe the COLETEK service. Luke and the team at COLETEK have taken our concepts to the next level.

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COLETEK have provided one to one communication throughout the development process and gone above and beyond in bringing our ideas closer to becoming a reality! Luke's expertise and knowledge with computer software and electronics is Jedi like, but what I liked most about working with him was his willingness and ability to think outside of the box.

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