Digitising construction
Construction technology has not seen any noticeable
improvement in over a 100 years. Though architects today are able to
design digitally with high precision, we still construct manually using
the same techniques that were used over a century ago. This disconnect
between digital design and the physical world has led to an economically
and environmentally unsustainable construction process, furthermore
producing buildings that are energy inefficient.
At Scaled Robotics our mission is to digitise construction.
Through the introduction of teams of mobile robots to the construction
site that work directly from the 3D model, we bridge the gap between
digital design and the physical construction site. This cuts out costly
errors and increases quality, transitioning to a leaner manufacturing
process.
Backed by our lead investor and industry partner Peri, we are modernising 21st century construction.
We are looking for passionate people to join our team, designing and testing robots for construction.
SLAM Engineer
Overview
Working as part of a team to implement SLAM for mobile
robots on the construction site. Getting your hands dirty building the
first robots for construction, pushing the boundaries of the industry.
Responsibilities:
- Implementing graph-based SLAM combining LIDAR and vision in challenging environments.
- Implementing map building for mobile platforms.
- Working closely with a broad spectrum of people,
including construction professionals to ensure a testable product is
being developed.
- Overseeing onsite evaluation and testing.
- Integrating SLAM with larger robotics navigation software.
- Understanding effects of mechanical and electrical design on SLAM system.
- Take initiative and push the systematic evaluation of algorithms
Qualifications
- Masters/PhD in Robotics or Computer Vision with
experience in SLAM and 3D reconstruction; alternatively comparable
industry career.
- At least 2-3 years experience developing algorithms
for graph-based SLAM, pose estimation, visual odometry, probabilistic
filtering and sensor fusion.
- Experience working with graph optimization backends for SLAM solutions (g2o, CERES).
- Experience working with wide variety of sensors, including RGBD Cameras, stereo cameras, LIDAR and TOF cameras.
- Experienced Object Oriented Programmer in C++ and Python.
- Experience with commonly used packages PCL, ROS, Gazebo, OpenCV.
- Experience with version control (specifically GIT).
- Experience developing in Linux.
- Publications at top robotics conferences (RSS, ICRA,
IROS) or 3D Vision and CV conferences (3DV, CVPR, ICCV, ECCV) in related
areas.
- Bonus: knowledge of GPU programming.
- Bonus: Open Source Software development and deployment.