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David St-Onge

Publications and source records attributed to David St-Onge.

24 records · Page 2Linked to original sources

Kinova Gen3-Lite manipulator inverse kinematics: optimal polynomial solution

A polynomial solution to the inverse kinematic problem of the Kinova Gen3 Lite robot is proposed in this paper. This serial robot is based on a 6R kinematic chain and is not wrist-partitioned. We first start from the forward kinematics equation providing the position and orientation of the end-effector, finally, the univariate polynomial equation is given as a function of the first joint variable $θ_{1}$. The remaining joint variables are computed by back substitution. Thus, an unique set of joint position is obtain for each root of the univariate equation. Numerical examples, simulated in ROS (Robot Operating System), are given to validate the results, which are compared to the coordinates obtained with MoveIt! and with the actual robot. A procedure to choose an optimum posture of the robot is also proposed.

cs.RO↗

Swarm Relays: Distributed Self-Healing Ground-and-Air Connectivity Chains

The coordination of robot swarms - large decentralized teams of robots - generally relies on robust and efficient inter-robot communication. Maintaining communication between robots is particularly challenging in field deployments. Unstructured environments, limited computational resources, low bandwidth, and robot failures all contribute to the complexity of connectivity maintenance. In this paper, we propose a novel lightweight algorithm to navigate a group of robots in complex environments while maintaining connectivity by building a chain of robots. The algorithm is robust to single robot failures and can heal broken communication links. The algorithm works in 3D environments: when a region is unreachable by wheeled robots, the chain is extended with flying robots. We test the performance of the algorithm using up to 100 robots in a physics-based simulator with three mazes and different robot failure scenarios. We then validate the algorithm with physical platforms: 7 wheeled robots and 6 flying ones, in homogeneous and heterogeneous scenarios.

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Decentralized Connectivity Control in Quadcopters: a Field Study of Communication Performance

Redundancy and parallelism make decentralized multi-robot systems appealing solutions for the exploration of extreme environments. However, effective cooperation often requires team-wide connectivity and a carefully designed communication strategy. Several recently proposed decentralized connectivity maintenance approaches exploit elegant algebraic results drawn from spectral graph theory. Yet, these proposals are rarely taken beyond simulations or laboratory implementations. In this work, we present two major contributions: (i) we describe the full-stack implementation---from hardware to software---of a decentralized control law for robust connectivity maintenance; and (ii) we assess, in the field, our setup's ability to correctly exchange all the necessary information required to maintain connectivity in a team of quadcopters.

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Collaborative Localization and Tracking with Minimal Infrastructure

Localization and tracking are two very active areas of research for robotics, automation, and the Internet-of-Things. Accurate tracking for a large number of devices usually requires deployment of substantial infrastructure (infrared tracking systems, cameras, wireless antennas, etc.), which is not ideal for inaccessible or protected environments. This paper stems from the challenge posed such environments: cover a large number of units spread over a large number of small rooms, with minimal required localization infrastructure. The idea is to accurately track the position of handheld devices or mobile robots, without interfering with its architecture. Using Ultra-Wide Band (UWB) devices, we leveraged our expertise in distributed and collaborative robotic systems to develop an novel solution requiring a minimal number of fixed anchors. We discuss a strategy to share the UWB network together with an Extended Kalman filter derivation to collaboratively locate and track UWB-equipped devices, and show results from our experimental campaign tracking visitors in the Chambord castle in France.

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Decentralized collaborative transport of fabrics using micro-UAVs

Small unmanned aerial vehicles (UAVs) have generally little capacity to carry payloads. Through collaboration, the UAVs can increase their joint payload capacity and carry more significant loads. For maximum flexibility to dynamic and unstructured environments and task demands, we propose a fully decentralized control infrastructure based on a swarm-specific scripting language, Buzz. In this paper, we describe the control infrastructure and use it to compare two algorithms for collaborative transport: field potentials and spring-damper. We test the performance of our approach with a fleet of micro-UAVs, demonstrating the potential of decentralized control for collaborative transport.

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ROS and Buzz: consensus-based behaviors for heterogeneous teams

This paper address the challenges encountered by developers when deploying a distributed decision-making behavior on heterogeneous robotic systems. Many applications benefit from the use of multiple robots, but their scalability and applicability are fundamentally limited if relying on a central control station. Getting beyond the centralized approach can increase the complexity of the embedded intelligence, the sensitivity to the network topology, and render the deployment on physical robots tedious and error-prone. By integrating the swarm-oriented programming language Buzz with the standard environment of ROS, this work demonstrates that behaviors requiring distributed consensus can be successfully deployed in practice. From simulation to the field, the behavioral script stays untouched and applicable to heterogeneous robot teams. We present the software structure of our solution as well as the swarm-oriented paradigms required from Buzz to implement a robust generic consensus strategy. We show the applicability of our solution with simulations and experiments with heterogeneous ground-and-air robotic teams.

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