17 accepted papers
As the field of robotics evolves, robots become increasingly multi-functional and complex. Currently, there is a need for solutions that enhance flexibility and computational power without compromising real-time performance. The emergence of fog computing and cloud-native approaches addresses these
This work presents a novel method for point registration in 3D space. The proposed algorithm utilizes transformation-invariant geometry information to estimate the pose of objects based on correspondences between points in two sets. Conventional methods use geometry descriptors to find these corresp…
Rotation invariance is a crucial property for 3D object classification, which is still a challenging task. State-of-the-art deep learning-based works require a massive amount of data augmentation to tackle this problem. This is however inefficient and classification accuracy suffers a sharp drop in…
Inferring a complete 3D geometry given an in-complete point cloud is essential in many vision and robotics applications. Previous work mainly relies on a global feature extracted by a Multi-layer Perceptron (MLP) for predicting the shape geometry. This suffers from a loss of structural details, as i…
This paper presents two different approaches to generate a time local-optimal and jerk-limited trajectory with blends for a robot manipulator under consideration of kinematic constraints. The first approach generates a trajectory with blends based on the trapezoidal acceleration model by formulating
We propose a surface-to-surface (S2S) point registration algorithm by exploiting the Gaussian Process Implicit Surfaces for partially overlapping 3D surfaces to estimate the 6D pose transformation. Unlike traditional approaches, that separate the corresponding search and update steps in the inner lo…
In this paper, we enhance our knowledge-based and constraint-based approach of robot programming with the concept of Semantic Mates. They describe intended mechanical connections between parts of an assembly. This allows deriving appropriate assembly poses from the type of connection and the geometr…
This paper presents an approach to generate the time-optimal trajectory for a robot manipulator under certain kinematic constraints such as joint position, velocity, acceleration, and jerk limits. This problem of generating a trajectory that takes the minimum time to pass through specified waypoints…
CAD/CAM approaches have been used in the manufacturing industry for a long time, and their use in robotic systems is becoming more popular. One common element in these approaches is the use of geometric constraints to define relative object poses. Hence, approaches for solving these geometric constr
We discuss the architecture and software engineering principles of the Robotics Library (RL). Driven by requirements of robot systems, research projects, industrial applications, and education, we identify relevant design requirements and present an approach to manage hardware and real-time, provide…
In this paper, we introduce a novel robot programming paradigm. It focuses on reducing the required expertise in robotics to a level that allows shop floor workers to use robots in their application domain without the need of extensive training. Our approach is user-centric and can interpret undersp…
In this paper, we propose a framework for prioritized constraint-based specification of robot tasks. This framework is integrated with a cognitive robotic system based on semantic models of processes, objects, and workcells. The target is to enable intuitive (re-)programming of robot tasks, in a way…
In this paper, we introduce an approach for leveraging CAD description to a semantic level, in order to link additional knowledge to CAD models and to exploit resulting synergy effects.
Intuitive programming of industrial robots is especially important for small and medium-sized enterprises. We evaluated four different input modalities (touch, gesture, speech, 3D tracking device) regarding their preference, usability, and intuitiveness for robot programming.
In this paper, we propose a framework for intuitive task-based programming of robots using geometric inter-relational constraints. The intended applications of this framework are robot programming interfaces that use semantically rich task descriptions, allow intuitive (re-)programming, and are suit…
In order to fully exploit the capabilities of a robotic systems, it is necessary to consider the limitations and errors of actuators and sensors already during the motion planning phase. In this paper, a framework for path planning is introduced, that uses heuristic search to build up a search graph…
The Space Exploration Guided Heuristic Search (SEHS) method solves the motion planning problem, especially for car-like robots, in two steps: a circle-based space exploration in the workspace followed by a circle-guided heuristic search in the configuration space. This paper extends this approach fo…