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Performance-based reactive navigation for non-holonomic mobile robots
2008
Robotica (Cambridge. Print)
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The planning problem is formulated as a constrained receding horizon planning problem and is solved in real time with an efficient computational method that combines nonlinear control theory, B-spline ...
Instead of addressing motion planning and control in different contexts, these issues are described in connected modules with performance requirement considerations. ...
To determine the motion equations on the sliding surface, the equivalent control method [21] is used. ...
doi:10.1017/s0263574708004700
fatcat:zim4gjqwend4jpyy53i5zfbobe
An Optimization-Based Receding Horizon Trajectory Planning Algorithm
[article]
2019
arXiv
pre-print
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This paper presents an optimization-based receding horizon trajectory planning algorithm for dynamical systems operating in unstructured and cluttered environments. ...
The resulting nominal trajectory is then improved in a second optimization-based receding horizon planning step which performs local trajectory refinement over a sliding time window. ...
Conclusions and Future Work This paper introduces a new two-step trajectory planning algorithm built on a combination of a search-based motion planning algorithm and an optimization-based receding horizon ...
arXiv:1912.05259v1
fatcat:ypackwowb5garh2tovdkht5nma
An Optimization-Based Receding Horizon Trajectory Planning Algorithm
2020
IFAC-PapersOnLine
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This paper presents an optimization-based receding horizon trajectory planning algorithm for dynamical systems operating in unstructured and cluttered environments. ...
The resulting nominal trajectory is then improved in a second optimization-based receding horizon planning step which performs local trajectory refinement over a sliding time window. ...
combination of a search-based motion planning algorithm and an optimization-based receding horizon planning (RHP) algorithm. ...
doi:10.1016/j.ifacol.2020.12.2399
fatcat:zyf2jx57xvgjrjk5nepbuijhri
INTEGRATION OF MOTION PLANNING AND MODEL-PREDICTIVE-CONTROL-BASED CONTROL SYSTEM FOR AUTONOMOUS ELECTRIC VEHICLES
2015
Transport
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This paper introduces the development of an autonomous driving system in autonomous electric vehicles, which consists of a simplified motion-planning program and a Model-Predictive-Control-Based (MPC-based ...
The motion-planning system is based on polynomial parameterization, which computes a path toward the expected longitudinal and lateral positions within required time interval in real scenarios. ...
Motion Planning This section describes the motion-planning method with a simplified kinematic vehicle model, as shown in Fig. 1 . δ is the front steering-wheel angle, (X(t), Y(t)) are the longitudinal ...
doi:10.3846/16484142.2015.1089322
fatcat:dm24onwgmba3rdsdrialooxxx4
MULTI-ROBOT MOTION PLANNING: A MODIFIED RECEDING HORIZON APPROACH FOR REACHING GOAL STATES
2016
Acta Polytechnica
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This paper proposes the real-time implementation of an algorithm for collision-free motion planning based on a receding horizon approach, for the navigation of a team of mobile robots in presence of obstacles ...
The method is simulated with three robots. Impact of parameters is studied with regard to computation time, obstacle avoidance and travel time. ...
The problem of producing a motion plan during a T c time interval is called here a receding horizon planning problem. ...
doi:10.14311/app.2016.56.0010
fatcat:k4d7mrp66bfvblwhacz3ronnym
Broadly-Exploring, Local-Policy Trees for Long-Horizon Task Planning
[article]
2020
arXiv
pre-print
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Classical motion planning algorithms, such as rapidly-exploring random trees, are capable of efficiently exploring large state spaces and computing long-horizon, sequential plans. ...
BELT uses an RRT-inspired tree search to efficiently explore the state space. ...
Others use models within classical algorithms, such as sampling-based motion planning [34] or control [35, 36] . ...
arXiv:2010.06491v1
fatcat:gy7xkdb4wzbbjiguhy5pqwxt2a
A Physics-Based Safety Recovery Approach for Fault-Resilient Multi-Quadcopter Coordination
[article]
2021
arXiv
pre-print
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For the high-level trajectory planning, first, we consider healthy quadcopters as particles of an irrotational fluid flow sliding along streamline paths wrapping failed quadcopters in the shared motion ...
Our approach consists of two main layers: (i) high-level physics-based guidance to safely plan the desired recovery trajectory for every healthy quadcopter and (ii) low-level trajectory control design ...
We develop a physics-based approach for recovery planning, and we verify the proposed method on dynamics of a group of quadcopters.
B. ...
arXiv:2110.07777v1
fatcat:r3nq5txmovb4ve4edtw7vwyaiy
Stability-constrained mobile manipulation planning on rough terrain
2022
Robotica (Cambridge. Print)
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Then, a sampling-based quasi-static planning algorithm modified for stability guarantee and traction optimization in continuous dynamic motion is presented along with a mathematical proof. ...
Qualitative and quantitative comparisons with existing methods are also presented. ...
The length of time interval in the new combined segment will be called "horizon length." For this specific example, the horizon length is chosen to be ≈ 4 s. ...
doi:10.1017/s0263574722000777
fatcat:irp5mboyz5a6bcfh4cu4pskfm4
A Motion Planning Framework with Connectivity Management for Multiple Cooperative Robots
2013
Journal of Intelligent and Robotic Systems
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This paper proposes a decentralized motion planning algorithm for multiple cooperative robots subject to constraints imposed by sensors and the communication network. ...
It consists of decentralized receding horizon planners that reside on each vehicle to navigate to individual target positions. ...
Receding Horizon Planner The motion planning problem is expressed as an optimal problem under constraint. ...
doi:10.1007/s10846-013-9872-0
fatcat:rnqptmqifva27fffj7vmgbrpeq
Uncertainty estimation of pedestrian future trajectory using Bayesian approximation
[article]
2022
arXiv
pre-print
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These future estimates can help an autonomous vehicle plan its trajectory and avoid collision. ...
However, under dynamic traffic scenarios, planning based on deterministic predictions is not trustworthy. ...
The uncertainty associated with predicted states can enable autonomous vehicles achieve uncertainty-aware motion planning that will be more robust and trustworthy compared to planning based on deterministic ...
arXiv:2205.01887v1
fatcat:oxmciurnvjholipuzjh7q3jngm
Tracking controllers for small UAVs with wind disturbances: Theory and flight results
2008
2008 47th IEEE Conference on Decision and Control
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This work features implementations of a spatial sliding mode controller and a receding-horizon kinodynamic controller. ...
The spatial sliding mode controller is designed to follow a desired aircraft path which places the camera-footprint on the desired locations, while the kinodynamic controller is designed to directly track ...
The high-level planning algorithm develops paths at 2 second intervals, with a 10 second planning horizon. ...
doi:10.1109/cdc.2008.4739415
dblp:conf/cdc/JacksonTKBH08
fatcat:smnju2345jbihaxjmhmjl3fvfa
Generating Continuous Motion and Force Plans in Real-Time for Legged Mobile Manipulation
[article]
2021
arXiv
pre-print
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This paper presents the Stability and Task Oriented Receding-Horizon Motion and Manipulation Autonomous Planner (STORMMAP) that is able to generate continuous plans for the robot's motion and manipulation ...
In contrast to existing state of the art methods, the approach described in this paper generates continuous plans in under ten milliseconds, an order of magnitude faster than previous strategies. ...
This paper describes a legged mobile manipulation planner, STORMMAP, which can compute plans for both the motion trajectory of the robot as well as the manipulation forces it exerts. ...
arXiv:2104.11685v1
fatcat:wshsubkkzjdhjjmdpfukddtolu
Development of an Adaptive and Weighted Model Predictive Control Algorithm for Autonomous Driving with Disturbance Estimation and Grey Prediction
2022
IEEE Access
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Based on the adaptive and weighted prediction method, the length of prediction horizon and cost value of each predicted state are adjusted in real time to eliminate any negative impact on future predicted ...
Therefore, an input weighting factor is adapted in the MPC cost function based on an exponential weighting function. ...
CONCLUSION This paper proposed an adaptive and weighted MPC algorithm for autonomous vehicles based on disturbance estimation with a sliding mode observer and the grey prediction method. ...
doi:10.1109/access.2022.3163309
fatcat:s5rbgxy5d5hu5cv7alkkn4lome
Generating Continuous Motion and Force Plans in Real-Time for Legged Mobile Manipulation
2021
2021 IEEE International Conference on Robotics and Automation (ICRA)
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DISCUSSION AND CONCLUSION This paper describes a legged mobile manipulation planner, STORMMAP, which can compute plans for both the motion trajectory of the robot as well as the manipulation forces it ...
By formulating the planner as a nonlinear optimization problem with pre-specified contact locations for the manipulator's end-effector, we can plan dynamically feasible motions and forces while ensuring ...
To the best of our knowledge, this is the fastest dynamic planning strategy in the literature based on planning speed by an order of magnitude [15] - [18] , [20] . ...
doi:10.1109/icra48506.2021.9561117
fatcat:bzwienzicrhlfpjmsy76hbyzze
Abstracts
2020
IEEE Transactions on Intelligent Vehicles
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Herein, a state observer-based modified sliding mode interval fuzzy type-2 neural network (FT2NN) controller is designed to suppress the vibrations from a typical rough terrain imposed to the nonlinear ...
In this article, we developed an assist method based on auditory presentation that indicates the timing for starting of steering in order to follow the target trajectory during reverse parking. ...
Adaptive Robust Nonlinear Active Suspension Control Using an Observer-Based Modified Sliding Mode Interval Type-2 Fuzzy Neural Network
Motion Planning With Velocity Prediction and Composite Nonlinear ...
doi:10.1109/tiv.2020.2971873
fatcat:af7apwjygrajxeenbiwv7grzii
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