23 accepted papers
Soft Actor-Critic (SAC) has achieved notable success in continuous control tasks but struggles in sparse reward settings, where infrequent rewards make efficient exploration challenging. While novelty-based exploration methods address this issue by encouraging the agent to explore novel states, they…
Many practically relevant robot grasping problems feature a target object for which all grasps are occluded, e.g., by the environment. Single-shot grasp planning invariably fails in such scenarios. Instead, it is necessary to first manipulate the object into a configuration that affords a grasp. We…
Stack-of-Tasks (SoT) control allows a robot to simultaneously fulfill a number of prioritized goals formulated in terms of (in)equality constraints in error space. Since this approach solves a sequence of Quadratic Programs (QP) at each time-step, without taking into account any temporal state evolu
Conventional methods to autonomous grasping rely on a pre-computed database with known objects to synthesize grasps, which is not possible for novel objects. On the other hand, recently proposed deep learning-based approaches have demonstrated the ability to generalize grasp for unknown objects. How…
In manufacturing, assembly tasks have been a challenge for learning algorithms due to variant dynamics of different environments. Reinforcement learning (RL) is a promising framework to automatically learn these tasks, yet it is still not easy to apply a learned policy or skill, that is the ability
Gaussian process (GP) implicit surface models provide environment and object representations which elegantly address noise and uncertainty while remaining sufficiently flexible to capture complex geometry. However, GP models quickly become intractable as the size of the observation set grows—a trait
Traditional approaches to manipulating the state of deformable linear objects (DLOs) - i.e., cables, ropes - rely on model-based planning. However, constructing an accurate dynamic model of a DLO is challenging due to the complexity of interactions and a high number of degrees of freedom. This rende…
Tracking of deformable linear objects (DLOs) is important for many robotic applications. However, achieving robust and accurate tracking is challenging due to the lack of distinctive features or appearance on the DLO, the object's high-dimensional state space, and the presence of occlusion. In this
Contact-rich manipulation tasks remain a hard problem in robotics that requires interaction with unstructured environments. Reinforcement Learning (RL) is one potential solution to such problems, as it has been successfully demonstrated on complex continuous control tasks. Nevertheless, current stat
Estimating the 6DOF pose of objects is an important function in many applications, such as robot manipulation or augmented reality. However, accurate and fast pose estimation from 3D point clouds is challenging, because of the complexity of object shapes, measurement noise, and presence of occlusion
Modeling dynamics of deformable linear objects (DLOs), such as cables, hoses, sutures, and catheters, is an important and challenging problem for many robotic manipulation applications. In this paper, we propose the first method to model and learn full 3D dynamics of DLOs from data. Our approach is…
Creating maps is an essential task in robotics and provides the basis for effective planning and navigation. In this paper, we learn a compact and continuous implicit surface map of an environment from a stream of range data with known poses. For this, we create and incrementally adjust an ensemble…
We present a system capable of reconstructing highly detailed object-level models and estimating the 6D pose of objects by means of an RGB-D camera. In this work, we integrate deeplearning-based semantic segmentation, instance segmentation, and 6D object pose estimation into a state of the art RGB-D
Warehouse logistics is a rapidly growing market for robots. However, one key procedure that has not received much attention is the unwrapping of pallets to prepare them for objects picking. In fact, to prevent the goods from falling and to protect them, pallets are normally wrapped in plastic when t
The ability to maintain and continuously update geometric calibration parameters of a mobile platform is a key functionality for every robotic system. These parameters include the intrinsic kinematic parameters of the platform, the extrinsic parameters of the sensors mounted on it, and their time de
Voxel volumes are simple to implement and lend themselves to many of the tools and algorithms available for 2D images. However, the additional dimension of voxels may be costly to manage in memory when mapping large spaces at high resolutions. While lowering the resolution and using interpolation is…
This article presents an approach for assisted teleoperation of a robot arm, formulated within a real-time stack-of-tasks (SoT)whole-body motion control framework. The approach leverages the hierarchical nature of the SoT framework to integrate operator commands with assistive tasks, such as joint l…
Local scan registration approaches commonly only utilize ego-motion estimates (e.g. odometry) as an initial pose guess in an iterative alignment procedure. This paper describes a new method to incorporate ego-motion estimates, including uncertainty, into the objective function of a registration algo…
With the increased availability of GPUs and multicore CPUs, volumetric map representations are an increasingly viable option for robotic applications. A particularly important representation is the truncated signed distance field (TSDF) that is at the core of recent advances in dense 3-D mapping. Ho
Grasping systems that build upon meticulously planned hand postures rely on precise knowledge of object geometry, mass and frictional properties — assumptions which are often violated in practice. In this work, we propose an alternative solution to the problem of grasp acquisition in simple autonomo…
So far, autonomous order picking (commissioning) systems have not been able to meet the stringent demands regarding speed, safety, and accuracy of real-world warehouse automation, resulting in reliance on human workers. In this letter, we target the next step in autonomous robot commissioning: autom
Given that 3D scan matching is such a central part of the perception pipeline for robots, thorough and large-scale investigations of scan matching performance are still surprisingly few. A crucial part of the scientific method is to perform experiments that can be replicated by other researchers in…
Autonomous navigation in real-world industrial environments is a challenging task in many respects. One of the key open challenges is fast planning and execution of trajectories to reach arbitrary target positions and orientations with high accuracy and precision, while taking into account non-holon…