About the role#
Construction sites change with every bucket of dirt. The State Estimation team builds the maps and localization systems that help autonomous excavators understand their position and how the terrain shifts. As an intern, you will explore how modern learning-based methods can improve our geometry-first mapping stack. You might focus on localizing reliably in repetitive terrain, building maps that withstand dust and occlusion, or labeling the map semantically so the machine can distinguish between haul roads, spoil piles, and berms. You will test ideas on real fleet data, measure them against classical baselines, and deliver a prototype for the team to build upon.
What you'll do#
- Prototype learned SLAM and mapping methods, including place recognition, odometry, depth completion, and neural occupancy or surface representations.
- Fuse lidar and camera segmentation into consistent 3D semantic maps, potentially using vision foundation models or open-vocabulary segmentation.
- Develop methods that handle changing terrain, moving material, sparse returns, dust, occlusion, and perceptual aliasing.
- Train models on fleet lidar and camera data, and build evaluation pipelines to compare mapping and localization performance against existing methods and ground truth.
- Work with perception and planning teams to identify the map properties that matter most for downstream decisions.
- Deliver a documented prototype, experimental results, and recommendations for future work.
What you'll need#
- Pursuing a BS, MS, or PhD in computer science, robotics, electrical engineering, or a related field, or equivalent research or industry experience.
- Strong Python skills and hands-on model training experience with PyTorch or a similar framework.
- Solid understanding of 3D geometry, coordinate frames, and transforms.
- Familiarity with SLAM and mapping fundamentals, point clouds, or depth data.
- Comfort with messy sensor data and designing experiments that distinguish real improvements from noise.
- Research or project experience in learned SLAM, semantic mapping, or 3D scene understanding.
- Experience with neural scene representations, such as NeRFs, 3D Gaussian splatting, neural occupancy, or signed distance fields.
- Experience applying vision foundation models, such as DINOv2 or SAM, to 3D or robotics problems.
- Experience with lidar processing or multi-sensor fusion.
- Exposure to autonomous vehicle, off-road, or field robotics data.
- Familiarity with Rust or C++, and ROS or similar robotics middleware.
Location & details#
- Location: San Francisco, California, United States.
- Term: Summer 2027.
- Modality: On-site.
- Employment: Full-time internship.
- Compensation: Paid position.
About Bedrock Robotics
Bedrock Robotics develops autonomous technology for the construction industry. The company modifies heavy machinery to perform tasks with increased safety and precision. It focuses on infrastructure projects like housing, data centers, and energy facilities. Founded in 2024, the business operates out of San Francisco with 160 employees.
How to get in at Bedrock Robotics
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