Multi-object Monocular SLAM for Dynamic Environments

  title={Multi-object Monocular SLAM for Dynamic Environments},
  author={Gokul B. Nair and Swapnil Daga and Rahul Sajnani and Anirudh Ramesh and Junaid Ahmed Ansari and K. Madhava Krishna},
  journal={2020 IEEE Intelligent Vehicles Symposium (IV)},
In this paper, we tackle the problem of multibody SLAM from a monocular camera. The term multibody, implies that we track the motion of the camera, as well as that of other dynamic participants in the scene. The quintessential challenge in dynamic scenes is unobservability: it is not possible to unambiguously triangulate a moving object from a moving monocular camera. Existing approaches solve restricted variants of the problem, but the solutions suffer relative scale ambiguity (i.e., a family… 
BirdSLAM: Monocular Multibody SLAM in Bird's-Eye View
BirdSLAM tackles challenges faced by other monocular SLAM systems by using an orthographic (bird's-eye) view as the configuration space in which localization and mapping are performed by assuming only the height of the ego-camera above the ground.
ClusterVO: Clustering Moving Instances and Estimating Visual Odometry for Self and Surroundings
ClusterVO is a stereo Visual Odometry which simultaneously clusters and estimates the motion of both ego and surrounding rigid clusters/objects, reaching comparable results to state-of-the-art solutions on both odometry and dynamic trajectory recovery.
A survey: which features are required for dynamic visual simultaneous localization and mapping?
A survey on dynamic SLAM from the perspective of feature choices is presented, which can provide more robust localization for intelligent robots that operate in complex dynamic environments.


Shape priors for real-time monocular object localization in dynamic environments
This paper presents a real-time monocular object localization system that estimates the shape and pose of dynamic objects in real- time, using video frames captured from a moving monocular camera, and presents a CNN architecture that performs precise keypoint localization.
Realtime multibody visual SLAM with a smoothly moving monocular camera
This paper presents a realtime, incremental multibody visual SLAM system that allows choosing between full 3D reconstruction or simply tracking of the moving objects, and enables building of a unified dynamic 3D map of scenes involving multiple moving objects.
LSD-SLAM: Large-Scale Direct Monocular SLAM
A novel direct tracking method which operates on \(\mathfrak{sim}(3)\), thereby explicitly detecting scale-drift, and an elegant probabilistic solution to include the effect of noisy depth values into tracking are introduced.
MonoSLAM: Real-Time Single Camera SLAM
The first successful application of the SLAM methodology from mobile robotics to the "pure vision" domain of a single uncontrolled camera, achieving real time but drift-free performance inaccessible to structure from motion approaches is presented.
CubeSLAM: Monocular 3-D Object SLAM
The SLAM method achieves the state-of-the-art monocular camera pose estimation and at the same time, improves the 3-D object detection accuracy.
Incremental real-time multibody VSLAM with trajectory optimization using stereo camera
This paper proposes an algorithm to jointly infer the camera trajectory and the moving object trajectory simultaneously simultaneously, and achieves exact incremental solution by solving a full nonlinear optimization problem in real time.
Reconstructing 3D trajectories of independently moving objects using generic constraints
This paper proposes to exploit the increased linear coupling between camera and object translations that tends to appear at false scales to provide a second, 'non-accidentalness' criterion for the selection of the correct motion among the one-parameter family.
ORB-SLAM: A Versatile and Accurate Monocular SLAM System
A survival of the fittest strategy that selects the points and keyframes of the reconstruction leads to excellent robustness and generates a compact and trackable map that only grows if the scene content changes, allowing lifelong operation.
ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras
ORB-SLAM2, a complete simultaneous localization and mapping (SLAM) system for monocular, stereo and RGB-D cameras, including map reuse, loop closing, and relocalization capabilities, is presented, being in most cases the most accurate SLAM solution.
Multibody Structure and Motion: 3-D Reconstruction of Independently Moving Objects
This paper extends the recovery of structure and motion to image sequences with several independently moving objects, where Euclidean reconstruction becomes possible in the multibody case, when it was underconstrained for a static scene.