Organizational Unit:

Humanoid Robotics Laboratory

Permanent Link

https://hdl.handle.net/1853/70718

Parent Organization

Organizational Unit

Institute for Robotics and Intelligent Machines (IRIM)

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Publication Search Results

Now showing 1 - 10 of 11

Robust and Efficient Communication for Real-Time Multi-Process Robot Software

(Georgia Institute of Technology, 2012-11) Dantam, Neil ; Stilman, Mike

We present a new Interprocess Communication (IPC) mechanism and library. Ach is uniquely suited for coordinating drivers, controllers, and algorithms in complex robotic systems such as humanoid robots. Ach eliminates the Head-of-Line Blocking problem for applications that always require access to the newest message. Ach is efficient, robust, and formally verified. It has been tested and demonstrated on a variety of physical robotic systems, and we discuss the implementation on our humanoid robot Golem Krang. Finally, the source code for Ach is available under an Open Source permissive license.
Linguistic Transfer of Human Assembly Tasks to Robots

(Georgia Institute of Technology, 2012-10) Dantam, Neil ; Essa, Irfan ; Stilman, Mike

We demonstrate the automatic transfer of an assembly task from human to robot. This work extends efforts showing the utility of linguistic models in verifiable robot control policies by now performing real visual analysis of human demonstrations to automatically extract a policy for the task. This method tokenizes each human demonstration into a sequence of object connection symbols, then transforms the set of sequences from all demonstrations into an automaton, which represents the task-language for assembling a desired object. Finally, we combine this assembly automaton with a kinematic model of a robot arm to reproduce the demonstrated task.
The Motion Grammar Calculus for Context-Free Hybrid Systems

(Georgia Institute of Technology, 2012-06) Dantam, Neil ; Stilman, Mike

This paper provides a method for deriving provably correct controllers for Hybrid Dynamical Systems with Context-Free discrete dynamics, nonlinear continuous dynamics, and nonlinear state partitioning. The proposed method models the system using a Context-Free Motion Grammar and specifies correct performance using a Regular language representation such as Linear Temporal Logic. The initial model is progressively rewritten via a calculus of symbolic transformation rules until it satisfies the desired specification.
Linguistic Composition of Semantic Maps and Hybrid Controllers

(Georgia Institute of Technology, 2012-06) Dantam, Neil ; Nieto-Granda, Carlos ; Christensen, Henrik I. ; Stilman, Mike

This work combines semantic maps with hybrid control models, generating a direct link between action and environment models to produce a control policy for mobile manipulation in unstructured environments. First, we generate a semantic map for our environment and design a base model of robot action. Then, we combine this map and action model using the Motion Grammar Calculus to produce a combined robot-environment model. Using this combined model, we apply supervisory control to produce a policy for the manipulation task. We demonstrate this approach on a Segway RMP-200 mobile platform.
Algorithms for Linguistic Robot Policy Inference from Demonstration of Assembly Tasks

(Georgia Institute of Technology, 2012) Dantam, Neil ; Essa, Irfan ; Stilman, Mike

We describe several algorithms used for the inference of linguistic robot policies from human demonstration. First, tracking and match objects using the Hungarian Algorithm. Then, we convert Regular Expressions to Nondeterministic Finite Automata (NFA) using the McNaughton-Yamada-Thompson Algorithm. Next, we use Subset Construction to convert to a Deterministic Finite Automaton. Finally, we minimize finite automata using either Hopcroft's Algorithm or Brzozowski's Algorithm.
Make Your Robot Talk Correctly: Deriving Models of Hybrid System

(Georgia Institute of Technology, 2011-07) Dantam, Neil ; Stilman, Mike ; Egerstedt, Magnus B.

Using both formal language and differential equations to model a robotic system, we introduce a calculus of transformation rules for the symbolic derivation of hybrid controllers. With a Context-Free Motion Grammar, we show how to test reachability between different regions of state-space and give several symbolic transformations to modify the set of event strings the system may generate. This approach lets one modify the language of the hybrid system, providing a way to change system behavior so that it satisfies linguistic constraints on correct operation.
The Motion Grammar: Linguistic Perception, Planning, and Control

(Georgia Institute of Technology, 2011-06) Dantam, Neil ; Stilman, Mike

We present and analyze the Motion Grammar: a novel unified representation for task decomposition, perception, planning, and control that provides both fast online control of robots in uncertain environments and the ability to guarantee completeness and correctness. The grammar represents a policy for the task which is parsed in real-time based on perceptual input. Branches of the syntax tree form the levels of a hierarchical decomposition, and the individual robot sensor readings are given by tokens. We implement this approach in the interactive game of Yamakuzushi on a physical robot resulting in a system that repeatably competes with a human opponent in sustained gameplay for the roughly six minute duration of each match.
Ach: IPC for Real-Time Robot Control

(Georgia Institute of Technology, 2011) Dantam, Neil ; Stilman, Mike

We present a new Inter-Process Communication (IPC) mechanism and library. Ach is uniquely suited for coordinating perception, control drivers, and algorithms in real-time systems that sample data from physical processes. Ach eliminates the Head-of-Line Blocking problem for applications that always require access to the newest message. Ach is efficient, robust, and formally verified. It has been tested and demonstrated on a variety of physical robotic systems. Finally, the source code for Ach is available under an Open Source BSD-style license.
Equations of Motion for Dynamically Stable Mobile Manipulators

(Georgia Institute of Technology, 2010-12-14) Dantam, Neil ; Kolhe, Pushkar ; Stilman, Mike
Dynamic Pushing Strategies for Dynamically Stable Mobile Manipulators

(Georgia Institute of Technology, 2010-05) Kolhe, Pushkar ; Dantam, Neil ; Stilman, Mike

This paper presents three effective manipulation strategies for wheeled, dynamically balancing robots with articulated links. By comparing these strategies through analysis, simulation and robot experiments, we show that contact placement and body posture have a significant impact on the robot's ability to accelerate and displace environment objects. Given object geometry and friction parameters we determine the most effective methods for utilizing wheel torque to perform non-prehensile manipulation.