Ronald C. Arkin

ICRA Conference 2023 Conference Paper

Hybrid SUSD-Based Task Allocation for Heterogeneous Multi-Robot Teams

• Shengkang Chen 0001
• Tony X. Lin
• Said Al-Abri
• Ronald C. Arkin
• Fumin Zhang 0001

Effective task allocation is an essential component to the coordination of heterogeneous robots. This paper proposes a hybrid task allocation algorithm that improves upon given initial solutions, for example from the popular decentralized market-based allocation algorithm, via a derivative-free optimization strategy called Speeding-Up and Slowing-Down (SUSD). Based on the initial solutions, SUSD performs a search to find an improved task assignment. Unique to our strategy is the ability to apply a gradient-like search to solve a classical integer-programming problem. The proposed strategy outperforms other state-of-the-art algorithms in terms of total task utility and can achieve near optimal solutions in simulation. Experimental results using the Robotarium are also provided.

IROS Conference 2022 Conference Paper

Multi-modal User Interface for Multi-robot Control in Underground Environments

• Shengkang Chen 0001
• Matthew Joseph O'Brien
• Fletcher Talbot
• Jason Williams 0002
• Brendan Tidd
• Alex Pitt
• Ronald C. Arkin

Leveraging both the autonomy of robots and the expert knowledge of humans can enable a multi-robot system to complete missions in challenging environments with a high degree of adaptivity and robustness. This paper proposes a multi-modal task-based graphical user interface for controlling a heterogeneous multi-robot team. The core of the interface is an integrated multi-robot task allocation system to allow the user to encode his/her intents to guide the heterogeneous multi-robot team. The design of the interface aims to provide the human operator continuous situational awareness and effective control for rapid decision-making in time-critical missions. Team CSIRO Data61 came in second place utilizing this interface for the DARPA Subterranean (SubT) Challenge. The ideas used for this user interface can apply to other multi-robot applications.

IROS Conference 2019 Conference Paper

Identifying Opportunities for Relationship-Focused Robotic Interventions in Strained Hierarchical Relationships *

• Michael J. Pettinati
• Ronald C. Arkin

When disagreements arise in hierarchical relationships, relationship members sometimes prefer conflict management strategies that avoid or quickly end the overt conflict even if the relationship is left in a state of dissatisfaction. Our lab has proposed that a peripheral robotic agent may be able to support these types of relationships during conflict. In this paper, we present the results of an IRB-approved human-robot interaction study that examines how the members of a hierarchical relationship involved in conflict respond to the presence of an unengaged robot. This study serves as a baseline for additional studies. The unengaged robot appears to have a minimal influence on the interaction. The observed conflicts followed the patterns typically described in mediation literature. Our lab previously proposed a computational model to identify weakness and alienation in these relationships. We discuss a partial implementation of this model, and its ability to recognize problems in certain relationships within the data collected. Based on our observations, and the performance of the model’s partial implementation, we suggest considerations that need to be made for an intervening robotic agent.

ICRA Conference 2017 Conference Paper

An intervening ethical governor for a robot mediator in patient-caregiver relationship: Implementation and evaluation

• Jaeeun Shim
• Ronald C. Arkin
• Michael Pettinatti

A robot mediator can enhance the quality of patient care in a health care context. Patients with Parkinson's disease can experience difficulties in precisely expressing their emotions due to the loss of control of their facial musculature, leading to their stigmatization by caregivers. To remedy this challenge, a robot mediator can be inserted into a patient-caregiver relationship. In this context, it is essential to handle the ethical issues of neglect to ensure human dignity. In an earlier paper [19], we proposed an intervening ethical governor (IEG) model, which enables a robot to ethically intervene in a situation where patients or caregivers go across accepted ethical boundaries. In this paper, we show how the IEG model can be implemented and applied in a real robotics system. In addition, by conducting interviews with the target population (adults 60 years of age or older), we evaluate the current intervention rules in the model, discuss potential improvements to the model, and consider uses of the model in real clinical contexts.

IROS Conference 2014 Conference Paper

Verifying and validating multirobot missions

• Damian M. Lyons
• Ronald C. Arkin
• Shu D. Jiang
• Dagan Harrington
• T. Liu

We have developed an approach that can be used by mission designers to determine whether or not a performance guarantee for their mission software, when carried out under the uncertain conditions of a real-world environment, will hold within a threshold probability. In this paper we demonstrate its utility for verifying multirobot missions, in particular a bounding overwatch mission.

IROS Conference 2013 Conference Paper

Getting it right the first time: Robot mission guarantees in the presence of uncertainty

• Damian M. Lyons
• Ronald C. Arkin
• P. Nirmal
• Shu D. Jiang
• Tsung-Ming Liu
• J. Deeb

Certain robot missions need to perform predictably in a physical environment that may only be poorly characterized in advance. We have previously developed an approach to establishing performance guarantees for behavior-based controllers in a process-algebra framework. We extend that work here to include random variables, and we show how our prior results can be used to generate a Dynamic Bayesian Network for the coupled system of program and environment model. Verification is reduced to a filtering problem for this network. Finally, we present validation results that demonstrate the effectiveness of the verification of a multiple waypoint robot mission using this approach.

IROS Conference 2012 Conference Paper

Designing autonomous robot missions with performance guarantees

• Damian M. Lyons
• Ronald C. Arkin
• P. Nirmal
• Shu D. Jiang

This paper describes the need and methods required to construct an integrated software verification and mission specification system for use in robotic missions intended for counter-weapons of mass destruction (c-WMD) operations, as part of a 3-year effort for the Defense Threat Reduction Agency. The overall system architecture is described. The principal tool for verification is a process algebra, PARS, based on port automata theory. PARS is introduced, emphasizing its ability to represent probabilistic programs and uncertain and dynamic environments, followed by the analysis of mission properties for an example robotic mission.

IS Journal 2012 Journal Article

Trends & Controversies

• Anton Nijholt
• Ronald C. Arkin
• Sebastien Brault
• Richard Kulpa
• Franck Multon
• Benoit Bideau
• David Traum
• Hayley Hung

Many applications require knowledge about how to deceive, including those related to safety, security, and warfare. Speech and text analysis can help detect deception, as can cameras, microphones, physiological sensors, and intelligent software. Models of deception and noncooperation can make a virtual or mixed-reality training environment more realistic, improve immersion, and thus make it more suitable for training military or security personnel. Robots might need to operate in physical and nontraining environments where they must perform military activity, including misleading the enemy. The contributions to this installment of Trends & Controversies present state-of-the-art research approaches to the analysis and generation of noncooperative and deceptive behavior in virtual humans, agents, and robots; the analysis of multiparty interaction in the context of deceptive behavior; and methods to detect misleading information in texts and computer-mediated communication. Articles include: "Computational Deception and Noncooperation, " by Anton Nijholt; "Robots that Need to Mislead: Biologically-Inspired Machine Deception, " by Ronald C. Arkin; "Deception in Sports Using Immersive Environments, " by Sébastien Brault, Richard Kulpa, Franck Multon, and Benoit Bideau; "Non-Cooperative and Deceptive Virtual Agents, " by David Traum; "Deception Detection in Multiparty Contexts, "by Hayley Hung; "Deception Detection, Human Reasoning, and Deception Intent, " by Eugene Santos Jr. , Deqing Li, and Fei Yu; and "Automatic Deception Detection in Computer-Mediated Communication, " by Lina Zhou and Dongsong Zhang.

ICRA Conference 2007 Conference Paper

Integrated Mission Specification and Task Allocation for Robot Teams - Design and Implementation

• Patrick Ulam
• Yoichiro Endo
• Alan R. Wagner
• Ronald C. Arkin

As the capabilities, range of missions, and the size of robot teams increase, the ability for a human operator to account for all the factors in these complex scenarios can become exceedingly difficult. Our previous research has studied the use of case-based reasoning (CBR) tools to assist a user in the generation of multi-robot missions. These tools, however, typically assume that the robots available for the mission are of the same type (i. e. , homogeneous). We loosen this assumption through the integration of contract-net protocol (CNP) based task allocation coupled with a CBR-based mission specification wizard. Two alternative designs are explored for combining case-based mission specification and CNP-based team allocation as well as the tradeoffs that result from the selection of one of these approaches over the other.

IROS Conference 2005 Conference Paper

Human perspective on affective robotic behavior: a longitudinal study

• Lilia Moshkina
• Ronald C. Arkin

Humans are inherently social creatures, and affect plays no small role in their social nature. We use our emotional expressions to communicate our internal state, our moods assist or hinder our interactions on a daily basis, we constantly form lasting attitudes towards others, and our personalities make us uniquely predisposed to perform certain tasks. In this paper, we present a framework under development that combines these four areas of affect to influence robotic behavior, and describe initial results of a longitudinal human-robot interaction study. The study was designed to inform the development of the framework in order to increase ease and pleasantness of human-robot interaction.

ICRA Conference 2005 Conference Paper

Reactive Speed Control System Based on Terrain Roughness Detection

• Mattia Castelnovi
• Ronald C. Arkin
• Thomas R. Collins

Autonomous outdoor navigation requires the ability to discriminate among different types of terrain. A non-trivial problem is to manage the robot’s speed based on terrain roughness. This paper presents a speed control system for a robotic platform traveling over natural terrain. This system is based on the view of a line-scanning laser of the area just in front of the platform. Analysis of range data for roughness produced by the laser over different terrains is examined. An algorithm for managing speed through different terrain has been tested on real outdoor surfaces producing excellent performance.

IROS Conference 2004 Conference Paper

Forgetting bad behavior: memory for case-based navigation

• Zsolt Kira
• Ronald C. Arkin

In this paper, we present successful strategies for forgetting cases in a case-based reasoning (CBR) system applied to autonomous robot navigation. This extends previous work that involved a CBR architecture, which indexes cases by the spatio-temporal characteristics of the sensor data, and outputs or selects parameters of behaviors in a behavior-based robot architecture. In such a system, the removal of cases can be applied when a new situation unlike any current case in the library is encountered, but the library is full. Various strategies of determining which cases to remove are proposed, including metrics such as how frequently a case is used and a novel spreading activation mechanism. Experimental results show that such mechanisms can increase the performance of the system significantly and allow it to essentially forget old environments in which it was trained in favor of new environments it is currently encountering. The performance of this new system is better than both a purely reactive behavior-based system as well as the CBR module that did not forget cases. Furthermore, such forgetting mechanisms can be useful even when there is no major environmental shift during training, since some cases can potentially be harmful or rarely used. The relationship between the forgetting mechanism and the case library size is also discussed.

ICRA Conference 2004 Conference Paper

Multi-robot Communication-sensitive Reconnaissance

• Alan R. Wagner
• Ronald C. Arkin

This paper presents a method for multi-robot communication sensitive reconnaissance. This approach utilizes collections of precompiled vector fields in parallel to coordinate a team of robots in a manner that is responsive to communication failures. Collections of vector fields are organized at the task level for reusability and generality. Different team sizes, scenarios, and task management strategies are investigated. Results indicate an acceptable reduction in communication attenuation when compared to other related methods of navigation. Online management of tasks and potential scalability are discussed.

ICRA Conference 2004 Conference Paper

Towards Performance Guarantees for Emergent Behavior

• Damian M. Lyons
• Ronald C. Arkin

It is important to be able to guarantee the safety and effectiveness of robot behavior in applications where robots must operate alongside people or in hazardous situations. A modeling framework based on port automata and asynchronous communication is introduced in this paper. By looking at the internal transitions between port communications, an analysis approach is developed that removes the combinatoric issues of looking at an asynchronous combination of robot and environment. An example application of the approach to wheel slippage in a mobile robot is presented.

ICRA Conference 2004 Conference Paper

When Good Communication Go Bad: Communications Recovery for Multi-robot Teams

• Patrick Ulam
• Ronald C. Arkin

Ad-hoc networks among groups of autonomous mobile robots are becoming a common occurrence as teams of robots take on increasingly complicated missions over wider areas. Research has often focused on proactive means in which the individual robots of the team may prevent communication failures between nodes in this network. This is not always possible especially in unknown or hostile environments. This research addresses reactive aspects of communication recovery. How should the members of the team react in the event of unseen communication failures between some or all of the nodes in the network? We present a number of behaviors to be utilized in the event of communications failure as well as a behavioral sequencer to further enhance the effectiveness of these recovery behaviors. The performance of the communication recovery behavior is analyzed in simulation and their application on hardware platforms is discussed.

IROS Conference 2003 Conference Paper

Adaptive multi-robot behavior via learning momentum

• J. Brian Lee
• Ronald C. Arkin

In this paper, the effects of adaptive robotic behavior via learning momentum in the context of a robotic team are studied. Learning momentum is a variation on parametric adjustment methods that has previously been successfully applied to enhance individual robot performance. In particular, we now assess, via simulation, the potential advantages of a team of robots using this capability to alter behavioral parameters when compared to a similar team of robots with static parameters.

IROS Conference 2003 Conference Paper

Anticipatory robot navigation by simultaneously localizing and building a cognitive map

• Yoichiro Endo
• Ronald C. Arkin

This paper presents a method for a mobile robot to construct and localize relative to a "cognitive map", where the cognitive map is assumed to be a representational structure that encodes both spatial and behavioral information. The localization is performed by applying a generic Bayes filter. The cognitive map was implemented within a behavior-based robotic system, providing a new behavior that allows the robot to anticipate future events using the cognitive map. One of the prominent advantages of this approach is elimination of the pose sensor usage (e. g. , shaft encoder, compass, GPS, etc.), which is known for its limitations and proneness to various errors. A preliminary experiment was conducted in simulation and its promising results are discussed.

IROS Conference 2003 Conference Paper

Internalized plans for communication-sensitive robot team behaviors

• Alan R. Wagner
• Ronald C. Arkin

Autonomous teams of robots operating in a dynamic, adversarial environment stand to benefit from using all available resources. But how can knowledge be used to construct a plan that does not interfere with the robots ability to react to its environment? In this research we distill abstract representation into a plan usable by a reactive behavior-based architecture. This plan is then exploited to enhance the performance of a team of robots tasked with maintaining communications while performing reconnaissance. Utilizing multiple plans in serial and in parallel is shown via simulation to be a promising method for increasing mission performance. We conclude that the utility of these internalized plans warrants further investigation as a method for imbuing reactive agents with a priori knowledge.

ICRA Conference 2003 Conference Paper

Learning to role-switch in multi-robot systems

• Eric Martinson
• Ronald C. Arkin

We present an approach that uses Q-learning on individual robotic agents, for coordinating a mission-tasked team of robots in a complex scenario. To reduce the size of the state space, actions are grouped into sets of related behaviors called roles and represented as behavioral assemblages. A role is a finite state automata such as Forager, where the behaviors and their sequencing for finding objects, collecting them, and returning them are already encoded and do not have to be re-learned. Each robot starts out with the same set of possible roles to play, the same perceptual hardware for coordination, and no contact other than perception regarding other members of the team. Over the course of training, a team of Q-learning robots will converge to solutions that best the performance of a well-designed handcrafted homogeneous team.

IROS Conference 2003 Conference Paper

Mobile robots at your fingertip: Bezier curve on-line trajectory generation for supervisory control

• Jung-Hoon Hwang
• Ronald C. Arkin
• Dong-Soo Kwon

A new interfacing method is presented to control mobile robot(s) in a supervised manner. Mobile robots often provide global position information to an operator. This research describes a method whereby the operator controls a mobile robot(s) using his finger or stylus via a touchpad or touch screen interface. Using a mapping between the robot's operational site and the input device, a human user can provide routing information for the mobile robot. Two algorithms have been developed to create the robot trajectory from the operator's input. Information regarding numerous path points is generated when the operator moves his finger/stylus. To prune away meaningless point information, a simple but powerful significant points extracting algorithm is developed. The resulting significant points are used as waypoints. An on-line piecewise cubic Bezier curves (PCBC) trajectory generation algorithm is presented to create a smooth trajectory for these significant points. As the method is based on distance and not on time, the velocity of mobile robot can be controlled easily within its allowable dynamic range. The PCBC trajectory can also be modified on the fly. Simulation results are presented to verify these newly developed methods.

ICRA Conference 2003 Conference Paper

Proprioceptive Control for a Robotic Vehicle over Geometric Obstacles

• Kenneth J. Waldron
• Ronald C. Arkin
• Douglas J. Bakkum
• Ernest Merrill
• Muhammad E. Abdallah

In this paper we describe a software system built to coordinate an autonomous vehicle with variable configuration ability operating in rough terrain conditions. The paper describes the system architecture, with an emphasis on the action planning function. This is intended to work with a proprioceptive algorithm that continuously coordinates wheel torques and suspension forces and positions to achieve optimal terrain crossing performance.

ICRA Conference 2002 Conference Paper

Learning Behavioral Parameterization using Spatio-Temporal Case-Based Reasoning

• Maxim Likhachev
• Michael Kaess
• Ronald C. Arkin

This paper presents an approach to learning an optimal behavioral parameterization in the framework of a case-based reasoning methodology for autonomous navigation tasks. It is based on our previous work on a behavior-based robotic system that also employed spatio-temporal case-based reasoning in the selection of behavioral parameters but was not capable of learning new parameterizations. The present method extends the case-based reasoning module by making it capable of learning new and optimizing the existing cases where each case is a set of behavioral parameters. The learning process can either be a separate training process or be part of the mission execution. In either case, the robot learns an optimal parameterization of its behavior for different environments it encounters. The goal of this research is not only to automatically optimize the performance of the robot but also to avoid the manual configuration of behavioral parameters and the initial configuration of a case library, both of which require the user to possess good knowledge of robot behavior and the performance of numerous experiments. The presented method was integrated within a hybrid robot architecture and evaluated in extensive computer simulations, showing a significant increase in the performance over a nonadaptive system and a performance comparable to a non-learning CBR system that uses a hand-coded case library.

IROS Conference 2002 Conference Paper

Robot behavioral selection using q-learning

• Eric Martinson
• Alexander Stoytchev
• Ronald C. Arkin

ICRA Conference 2002 Conference Paper

Selection of Behavioral Parameters: Integration of Discontinuous Switching via Case-Based Reasoning with Continuous Adaptation via Learning Momentum

• J. Brian Lee
• Maxim Likhachev
• Ronald C. Arkin

This paper studies the effects of the integration of two learning algorithms, case-base reasoning (CBR) and learning momentum (LM), for the selection of behavioral parameters in real-time for robotic navigational tasks. Use of CBR methodology in the selection of behavioral parameters has already shown significant improvement in robot performance as measured by mission completion time and success rate. It has also made unnecessary the manual configuration of behavioral parameters from a user. However, the choice of the library of CBR cases does affect the robot performance, and choosing the right library sometimes is a difficult task especially when working with a real robot. In contrast, learning momentum does not depend on any prior information such as cases and searches for the "right" parameters in real-time. This results in high mission success rates and requires no manual configuration of parameters, but it shows no improvement in mission completion time. This work combines the two approaches so that CBR discontinuously switches behavioral parameters based on given cases whereas LM uses these parameters as a starting point for the real-time search for the "right" parameters. The integrated system was extensively evaluated on both simulated and physical robots. The tests showed that on simulated robots the integrated system performed as well as the CBR only system and outperformed the LM only system, whereas on real robots it significantly outperformed both CBR only and LM only systems.

ICRA Conference 2001 Conference Paper

Ethological Modeling and Architecture for an Entertainment Robot

• Ronald C. Arkin
• Masahiro Fujita
• Tsuyoshi Takagi
• Rika Hasegawa

Presents a method for creating high-fidelity models of animal behavior for use in robotic systems based on a behavioral systems approach, and describes in particular how an ethological model of a domestic dog can be implemented with AIBO, the Sony entertainment robot.

ICRA Conference 2001 Conference Paper

Implementing Tolman's Schematic Sowbug: Behavior-Based Robotics in the 1930's

• Yoichiro Endo
• Ronald C. Arkin

This paper re-introduces and evaluates the schematic sowbug proposed by Tolman (1939). The schematic sowbug is based on Tolman's purposive behaviorism, and it is believed to be the first prototype in history that actually implemented a behavior-based architecture suitable for robotics. The schematic sowbug navigates the environment based on two types of vectors, orientation and progression, that are computed from the values of sensors perceiving stimuli. Our experiments on both simulation and real robot proved the legitimacy of Tolman's assumptions, and the potential of applying the schematic sowbug model and principles within modern robotics is recognized.

ICRA Conference 2001 Conference Paper

Learning Momentum: Integration and Experimentation

• James B. Lee
• Ronald C. Arkin

We further study the effects of learning momentum as defined by Arkin, Clark and Ram (1992) on robots, both simulated and real, attempting to traverse obstacle fields in order to reach a goal. Integration of these results into a large-scale software architecture, MissionLab, provides the ability to exercise these algorithms in novel ways. Insight is also sought in reference to when different learning momentum strategies should be used.

ICRA Conference 2001 Conference Paper

Spatio-Temporal Case-Based Reasoning for Behavioral Selection

• Maxim Likhachev
• Ronald C. Arkin

Presents the application of a case-based reasoning approach to the selection and modification of behavioral assemblage parameters. The goal of this research is to achieve an optimal parameterization of robotic behaviors in run-time. This increases robot performance and makes a manual configuration of parameters unnecessary. The case-based reasoning module selects a set of parameters for an active behavioral assemblage in real-time. This set of parameters fits the environment better than hand-coded ones, and its performance is monitored providing feedback for a possible reselection of the parameters. The paper places a significant emphasis on the technical details of the case-based reasoning module and how it is integrated within a schema-based reactive navigation system. The paper also presents the results and evaluation of the system in both in simulation and real world robotic experiments.

ICRA Conference 1996 Conference Paper

Behavior-based mobile manipulation for drum sampling

• Douglas C. MacKenzie
• Ronald C. Arkin

This paper describes an implementation of a behavior-based mobile manipulator capable of autonomously transferring a sample from one drum to a second in unstructured environments. A major contribution of the project was the coherent integration of the arm and base as a cohesive unit, and not just a mobile base with an arm attached. The support for smooth simultaneous operation of all joints on the vehicle facilitated biologically plausible motions, such as arm preshaping. The behavior-based controller used a pseudo-force model, where behaviors add forces and torques to joints and limbs resulting in coordinated motion. The vehicle Jacobian is used to convert the pseudo-forces into joint torques and a pseudo-damping model converts the joint torques into joint velocities. This process allows rapid control of the manipulator without the use of inverse kinematics. A drum sampling task is presented where the vehicle demonstrates how a sample of material could be moved from one drum to another, illustrating the efficacy of the solution.

IROS Conference 1995 Conference Paper

Specification and execution of multiagent missions

• Douglas C. MacKenzie
• Jonathan M. Cameron
• Ronald C. Arkin

Specifying a multiagent behavioral configuration requires both a careful choice of the behavior set and creation of a temporal chain executing the mission using those behaviors. This difficult task is simplified by applying an object-oriented approach to the design using a methodology called temporal sequencing to partition the mission into discrete operating states and enumerate the perceptual triggers causing transitions between those states. Several smaller independent configurations (assemblages) can then be created, each implementing one distinct operating state. Each assemblage consists of a collection of behaviors and a suitable coordination mechanism which causes the group to act as a single, coherent, behavior. The missions are specified in a structured user-friendly language targeted for military-style scout missions. Various multiagent missions have been demonstrated in simulation and results are shown using our Denning mobile robots.

IROS Conference 1994 Conference Paper

Model-based echolocation of environmental objects

• Juan Carlos Santamaría
• Ronald C. Arkin

This paper presents an algorithm that can recognize and localize objects given a model of their contours using only ultrasonic range data. The algorithm exploits a physical model of the ultrasonic beam and combines several readings to extract outline object segments from the environment. It then detects patterns of outline segments that correspond to predefined models of object contours, performing both object recognition and localization. The algorithm is robust since it can account for noise and inaccurate readings as well as efficient since it uses a relaxation technique that can incorporate new data incrementally without recalculating from scratch. >

ICRA Conference 1992 Conference Paper

Learning momentum: online performance enhancement for reactive systems

• Russell J. Clark 0001
• Ronald C. Arkin
• Ashwin Ram 0001

The authors describe a reactive robotic control system which incorporates aspects of machine learning to improve the system's ability to navigate successfully in unfamiliar environments. This system overcomes limitations of completely reactive systems by exercising online performance enhancement without the need for high-level planning. The goal of the learning system is to give the autonomous robot the ability to adjust the scheme control parameters in an unstructured dynamic environment. The results of a successful implementation that learns to navigate out of a box canyon are presented. This system never resorts to a high-level planner, but instead learns continuously by adjusting gains based on the progress made so far. The system is successful because it is able to improve its performance in reaching a goal in a previously unfamiliar and dynamic world. >

IROS Conference 1992 Conference Paper

Sfx: An Architecture For Action-oriented Sensor Fusion

• Robin R. Murphy
• Ronald C. Arkin

IROS Conference 1992 Conference Paper

The Learning Of Reactive Control Parameters Through Genetic Algorithms

• Michael Pearce
• Ronald C. Arkin
• Ashwin Ram 0001

IROS Conference 1990 Conference Paper

Qualitative spatial understanding and reactive control for autonomous robots

• Daryl T. Lawton
• Ronald C. Arkin
• Jonathan M. Cameron

The work involves integrating two paradigms for robust robotic systems: reactive control and qualitative spatial reasoning. The objective is to produce autonomous robots which can freely wander about, without harming themselves, while creating and improving maps of their environment which can then be used for navigation and planning. Reactive control provides a basic framework for developing and organizing behaviors for autonomous exploration and navigation. Qualitative spatial understanding provides an underlying representation and learning mechanism which will let the robot form spatial memories without requiring complicated object recognition or precise determination of environmental locations. The overall goal is to advance both areas of study for robotics as pertains to planning, learning, and real-time control.

ICRA Conference 1990 Conference Paper

Reactive inclinometer-based mobile robot navigation

• Ronald C. Arkin
• Warren F. Gardner

The authors have developed reactive motor behaviors (schemas) which exploit inclinometer data. Using this information, they have implemented artificial intelligence hill-climbing techniques as well as valley finding and isocontour following. All of these schemas are integrated with the other schemas present in the system AuRA (autonomous robot architecture) and can be used concurrently with obstacle avoidance, goal seeking, and other motor behaviors. Simulation studies illustrate the utility of these methods using actual terrain data. >

ICRA Conference 1989 Conference Paper

Dynamic replanning for a mobile robot based on internal sensing

• Ronald C. Arkin

Schema-based navigational techniques are used to introduce dynamic path replanning for a mobile robot, based on internal sensor information. This mode of operation, termed homeostatic control, forms an integral part of the autonomous robot architecture. A model that is analogous to the mammalian endocrine system serves as the basis for this mode. Simulation results verify the viability of this concept. It is found that dynamic replanning can be carried out using internal monitoring of the robot's state, and not solely based on environmental perception. The robot can be shown to be responsive to changes in fuel, temperature, and other conditions as it navigates through the world. >

IROS Conference 1989 Conference Paper

Mobile Robot Docking Operations in a Manufacturing Environment: Progress in Visual Perceptual Strategies

• Ronald C. Arkin
• Robin R. Murphy
• Mark Pearson
• David Vaughn

ICRA Conference 1987 Conference Paper

Motor schema based navigation for a mobile robot: An approach to programming by behavior

• Ronald C. Arkin

Motor schemas are proposed as a basic unit of behavior specification for the navigation of a mobile robot. These are multiple concurrent processes which operate in conjunction with associated perceptual schemas and contribute independently to the overall concerted action of the vehicle. The motivation behind the use of schemas for this domain is drawn from neuroscientific, psychological and robotic sources. A variant of the potential field method is used to produce the appropriate velocity and steering commands for the robot. An implementation strategy based on available tools at UMASS is described. Simulation results show the feasibility of this approach.