11 accepted papers
Robot motion planning via probabilistic inference renders a unique viewpoint on the trajectory optimization problem, in which the joint distribution of motion objectives is represented as a factor graph. Thus, the objectives are solved by obtaining the Maximum a Posteriori of the factor graph. While
Grasping fragile objects in the presence of un-certainty is a crucial task for robots, that becomes inherently challenging if the manipulator in use is an industrial robot platform that does not provide compliant control inputs. This requires not only to estimate the alignment error during object co…
We propose a novel method to tackle the visual-inertial localization problem for constrained camera movements. We use residuals from the different modalities to jointly optimize a global cost function. The residuals emerge from IMU measurements, stereoscopic feature points, and constraints on possib…
Redundant robots offer the possibility of improving agility, compared to their non-redundant counterparts, by exploiting the additional kinematic DOFs to increase a measure called manipulability. While it is common to maximize the manipulability measure during redundancy resolution locally, global o…
Gaussian Process (GP) formulation of continuous-time trajectory offers a fast solution to the motion planning problem via probabilistic inference on factor graph. However, often the solution converges to in-feasible local minima and the planned trajectory is not collision-free. We propose a message…
A key problem in robotics is enabling an autonomous agent to perform human-like arm movements in close proximity to another human. However, modeling the human decision and control process of the movement during dyadic interaction presents a challenge. Although, most prior approaches rely on multicom
With the integration of Human-Robot Collaboration (HRC) in industrial assembly scenarios, robot systems face numerous challenges. In contrast to classic robot systems which follow a pre-programmed and fixed sequence of actions, an interaction scenario with humans in the loop requires mutual adaptati…
With the increasing demand of humans and robots collaborating in a confined workspace, it is essential that robots can react instantaneously to unforeseen events while respecting comfort of human co-workers. As the human pays especial attention to the end-effector movement rather than individual joi…
The objective of this letter is to develop a data-driven model of laser intensities and investigate its usage for simultaneous localization and mapping (SLAM) in the field of robotics. In contrast to the standard usage of laser scanners in SLAM to generate geometric models of the environment, the re
This paper presents an extension of the standard occupancy grid for 3D environment mapping. The presented approach adds a fusion process after the occupancy update which modifies the resolution of the grid cells in an incremental manner. Consequently, the proposed approach requires fewer grid cells…
In robotics applications such as SLAM (Simultaneous Localization and Mapping), loop closure detection is an integral component required to build a consistent topological or metric map. This paper presents an appearance based loop closure detection mechanism titled `IBuILD' (Incremental bag of BInary…