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Jason Harris

dblp:144/5603 · DBLP profile ↗
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3ranked-venue papers
1as first author
3since 2021 · last 2022
0000-0001-8951-9877ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 1 first-author · 2 since 2021Systems, architecture and hardware · 2 · 1 first-author · 2 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
dexterous manipulation
0.612022
RBO Hand 3: A Platform for Soft Dexterous Manipulation · IEEE Trans. Robotics 2022
Robotics › Robot manipulation
grasping
0.612022
RBO Hand 3: A Platform for Soft Dexterous Manipulation · IEEE Trans. Robotics 2022
Robotics › Robot manipulation › grasping › grasp representation
grasp taxonomy
0.612022
RBO Hand 3: A Platform for Soft Dexterous Manipulation · IEEE Trans. Robotics 2022
Robotics › Robot manipulation › robotic hand
soft robotic hand
0.612022
RBO Hand 3: A Platform for Soft Dexterous Manipulation · IEEE Trans. Robotics 2022
Robotics › Robot manipulation › robotic hand design
anthropomorphic hand design
0.212022
RBO Hand 3: A Platform for Soft Dexterous Manipulation · IEEE Trans. Robotics 2022

Methods — techniques the papers use, named apart from their topics

pneumatic actuation · 0.6modular design · 0.6intrinsic compliance · 0.6
YearPublicationVenuePosition
2022 FC3: Feasibility-Based Control Chain Coordination
abstract
Hierarchical coordination of controllers often uses symbolic state representations that fully abstract their underlying low-level controllers, treating them as “black boxes” to the symbolic action abstraction. This paper proposes a framework to realize robust behavior, which we call Feasibility-based Control Chain Coordination (FC3). Our controllers expose the geometric features and constraints they operate on. Based on this, FC3can reason over the controllers' feasibility and their sequence feasibility. For a given task, FC3first automatically constructs a library of potential controller chains using a symbolic action tree, which is then used to coordinate controllers in a chain, evaluate task feasibility, as well as switching between controller chains if necessary. In several real-world experiments we demonstrate FC3, s robustness and awareness of the task's feasibility through its own actions and gradual responses to different interferences.
Jason Harris, Danny Drieß, Marc Toussaint
IROS1
2022 Sequence-of-Constraints MPC: Reactive Timing-Optimal Control of Sequential Manipulation
abstract
Task and Motion Planning has made great progress in solving hard sequential manipulation problems. However, a gap between such planning formulations and control methods for reactive execution remains. In this paper we pro-pose a model predictive control approach dedicated to robustly execute a single sequence of constraints, which corresponds to a discrete decision sequence of a TAMP plan. We decompose the overall control problem into three sub-problems (solving for sequential waypoints, their timing, and a short receding horizon path) that each is a non-linear program solved online in each MPC cycle. The resulting control strategy can account for long-term interdependencies of constraints and reactively plan for a timing-optimal transition through all constraints. We additionally propose phase backtracking when running constraints of the current phase cannot be fulfilled, leading to a fluent re-initiation behavior that is robust to perturbations and interferences by an experimenter.
Marc Toussaint, Jason Harris, Jung-Su Ha, Danny Drieß, Wolfgang Hönig
IROS2
2022 RBO Hand 3: A Platform for Soft Dexterous Manipulation
abstract
In this article, we present theRBO Hand 3, a highly capable and versatile anthropomorphic soft hand based on pneumatic actuation. TheRBO Hand 3is designed to enable dexterous manipulation, to facilitate transfer of insights about human dexterity, and to serve as a robust research platform for extensive real-world experiments. It achieves these design goals by combining many degrees of actuation with intrinsic compliance, replicating relevant functioning of the human hand, and by combining robust components in a modular design. TheRBO Hand 3possesses 16 independent degrees of actuation, implemented in a dexterous opposable thumb, two-chambered fingers, an actuated palm, and the ability to spread the fingers. In this article, we derive the design objectives that are based on experimentation with the hand’s predecessors, observations about human grasping, and insights about principles of dexterity. We explain in detail how the design features of theRBO Hand 3achieve these goals and evaluate the hand by demonstrating its ability to achieve the highest possible score in the Kapandji test for thumb opposition, to realize all 33 grasp types of the comprehensive GRASP taxonomy, to replicate common human grasping strategies, and to perform dexterous in-hand manipulation.
Steffen Puhlmann, Jason Harris, Oliver Brock
IEEE Trans. Robotics2