14 accepted papers
Collision-avoiding motion planning for articulated robotic arms is one of the major challenges in robotics. The difficulty of the problem arises from its high dimensionality and the intricate geometry of the feasible space. Our goal is to seek large convex domains in configuration space, which conta…
Task and motion planning is one of the key problems in robotics today. It is often formulated as a discrete task allocation problem combined with continuous motion planning. Many existing approaches to TAMP involve explicit descriptions of task primitives that cause discrete changes in the kinematic…
Mobile robots are becoming safer and more affordable, and their presence in the workspace is increasing. However, many tasks that involve reasoning, long-term planning or human preferences are still hard to automate. While some solutions in specialised areas slowly emerge, an alternative to full aut…
A central aspect of robotic motion planning is collision avoidance, where a multitude of different approaches are currently in use. Optimization-based motion planning is one method, that often heavily relies on distance computations between robots and obstacles. These computations can easily become…
A variety of control tasks such as inverse kinematics (IK), trajectory optimization (TO), and model predictive control (MPC) are commonly formulated as energy minimization problems. Numerical solutions to such problems are well-established. However, these are often too slow to be used directly in re
Multi-Robot Systems (MRS) present many advantages over single robots, e.g. improved stability and payload capacity. Being able to operate or teleoperate these systems is therefore of high interest in industries such as construction or logistics. However, controlling the collective motion of a MRS ca…
Many path planning algorithms are based on sampling the state space. While this approach is very simple, it can become costly when the obstacles are unknown, since samples hitting these obstacles are wasted. The goal of this paper is to efficiently identify obstacles in a map and remove them from th…
Due to their complex dynamics and high-dimensional configuration spaces, non-rigid objects such as cables, garments, bedding and various food items remain notoriously challenging for robots to manipulate effectively. In this letter, we therefore develop, validate and analyze model-based optimal cont
We combine Boston Dynamics Spot® with a light-weight, external robot arm to perform dynamic grasping maneuvers. While Spot is a reliable, robust and easy-to-control mobile robot, these highly desirable qualities come with the price that the control access granted to the user is restricted. Consequen…
Teleoperation provides a way for human operators to guide robots in situations where full autonomy is challenging or where direct human intervention is required. It can also be an important tool to teach robots in order to achieve autonomous behaviour later on. The increased availability of collabor…
Teleoperating robotic arms is a challenging task that requires years of training to master. It is mentally demanding, as the operator must internally compute transformations, or rely on muscle memory, to perform even the simplest tasks. Alternative methods that rely on embodiment –the immersive, fir…
We present an optimization framework for grasp and motion planning in the context of robotic assembly. Typically, grasping locations are provided by higher level planners or as input parameters. In contrast, our mathematical model simultaneously optimizes motion trajectories, grasping locations, and
Compliance is a defining characteristic of biological systems. Understanding how to exploit soft materials as effectively as living creatures do is consequently a fundamental challenge that is key to recreating the complex array of motor skills displayed in nature. As an important step towards this…
In this paper, we address the challenge of robotic manipulation of elastically deforming objects. To this end, we model elastic objects using the Finite Element Method. Through a quasi-static assumption, we leverage sensitivity analysis to mathematically model how changes in the robot's configuratio…